Integrated modelsfor defect free casting

(Deffree)

doi:10.2777/57608

Integrated models for defect free casting (D

effree)EU

EUR 25874

KI-NA-25874-EN

-N

The objective of the project was to develop a new modelling-based optimisation and quality control system for continuous casting. The concept was based on studying critical parameters affecting steel quality and finding safety ranges for them to ensure good quality in continuous casting.

Several fundamental and semi-empirical models were developed in the project. The critical features affecting steel quality were defined through mathematical modelling and industrial casting trials. Both good quality casts and casts with some defects were simulated to find features which have an effect on steel quality. Cracking indices, fluid flow parameters in the mould and segregation severity parameters are examples of critical parameters defined in the project. Safety ranges inside which the critical parameters had to stay during casting were determined in steady-state casting conditions. If a critical feature could not be adjusted on-line during casting, for example, surface velocity of liquid in the mould, this feature was expressed as a function of casting parameter, e.g. casting speed, which can be controlled and modified during casting.

For optimising and controlling steel quality during casting the following online models were developed in the project: transient 2D centreline segregation model, dynamic 3D heat transfer model and inverse mould heat flux difference model. These models can be applied also to other casters for online simulation, once the caster has been set up and casting process data is available.

Studies and reports

Research and Innovation EUR 25874 EN

EUROPEAN COMMISSION Directorate-General for Research and Innovation Directorate G — Industrial Technologies Unit G.5 — Research Fund for Coal and Steel

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European Commission

Research Fund for Coal and SteelIntegrated models for defect free casting

(Deffree)

S. Louhenkilpi, H. KytönenAalto University (AALTO)

School of Chemical Technology, PO Box 11000 (Otakaari 1), 00076 AALTO, Espoo, FINLAND

M. De Santis, S. Fraschetti, A. Gotti, M. R. Ridolfi, P. VescovoCentro Sviluppo Materiali S.p.A (CSM)

Via di Castel Romano 100, 00128 Rome, ITALY

R. KoitzschVDEh-Betriebsforschungsinstitut GmbH (BFI)

PO Box 105145, Sohnstraße 65, 40237 Düsseldorf, GERMANY

E. Balducci, C. AndrianopoliCogne Acciai Speciali S.P.A.Socio Unico (CAS)

Via Paravera 16, 11100 Aosta, ITALY

G. Martin, A. MolloDuferco Belgium S.A. (DUFERCO)

Rue Anna Boch 34, 7100 La Louvière, BELGIUM

Z. Csepeli, R. Josza, M. RégerISD Dunaferr Dunai Vasmű Zártkörűen Működő Részvénytársaság Zrt. (DUNAFERR)

PO Box 110, Vasműtér 1-3, 2400 Dunaújváros, HUNGARY

Grant Agreement RFSR-CT-2008-00007 1 July 2008 to 31 December 2011

Final report

Directorate-General for Research and Innovation

2013 EUR 25874 EN

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TABLE OF CONTENT

1 FINAL SUMMARY ..................................................................................................................................... 5 1.1 Objectives of the project ............................................................................................................................ 5 1.2. Work done and results .............................................................................................................................. 5

1.2.1 WP1 Definition of reference casting conditions .................................................................. 5 1.2.2 WP2 Simulation of mould powder behaviour ..................................................................... 6 1.2.3 WP3 Simulation of fluid flow and solidification behaviour ................................................ 7 1.2.4 WP4 Simulation of phase transformation ............................................................................ 9 1.2.5 WP5 Model application and validation in steady-state condition ....................................... 9 1.2.6 WP6 Development and application of the empiric on-line model optimised for process

control .................................................................................................................................. 12

2 SCIENTIFIC AND TECHNICAL DESCRIPTION OF RESULTS..................................... ............ .....15 2.1 Objectives of the project.......................................................................................................... ......... .....15 2.2 Comparison of initially planned activities and work accomplished. ...................................................... 16 2.3 Description of activities and discussion............................................................................................. ....16

2.3.1 WP1 Definition of reference casting conditions ................................................................ 16 2.3.2 WP2 Simulation of mould powder behaviour .................................................................... 22 2.3.3 WP3 Simulation of fluid flow and solidification behaviour .............................................. 35 2.3.4 WP4 Simulation of phase transformation .......................................................................... 49 2.3.5 WP5 Model application and validation in steady-state condition ..................................... 53 2.3.6 WP6 Development and application of the empiric on-line model optimised for process ......................................................................................................... 111

2.4 Conclusions ............................................................................................................................................ 123 2.5 Exploitation and impact of the research results .................................................................................... 125 3 List of Figures and Tables......................................................................................................................... 126

4 List of References ..................................................................................................................................... 130

List of Symbols ............................................................................................................................................ 132

Appendix 1 – Appendix Figures and Tables ............................................................................................... 133 Appendix 2 – Deliverables........................................................................................................................... 139 Appendix 3 - Critical parameters and safety ranges .................................................................................. 141 Appendix 4 - General description of the Liquid Motion Intensity (LMI) model by OBUDA and DUNAFERR ................................................................................................................................................ 146

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1 FINAL SUMMARY Introduction

DEFFREE project was a collaboration b etween Aalto University, CSM, BFI, C ogne Acciai Speciali, Duferco Belgium and ISD Dunaferr, as wel l as i ts s ubcontractors Ob uda U niversity an d C ollege o f Dunaujvaros. The project was coordinated by Aalto. The o utcome o f each t ask i s s ummarised b elow i n chapter “1 Final summary”. M ore d etailed descriptions o f wo rk d one an d t he r esults ar e i n ch apter 2 “Scientific and te chnical d escription of results”. Deliverables and reported in Appendix 2. “Conclusions of the project” and “Exploitation and impact of research results are given in the end of the report. 1.1 Objectives of the project The m ain o bjective o f t he p roject was t o de velop a ne w m odelling ba sed o ptimisation a nd quality control s ystem f or c ontinuous casting. The new concept is based on critical parameters a ffecting t he steel quality and finding safety ranges for the parameters in order to ensure good quality in continuous casting. T hese c ritical p arameters were o btained f rom casting e xperiments an d f rom mathematical models. 1.2 Work done and results 1.2.1 WP1 DEFINITION OF REFERENCE CASTING CONDITIONS Objective of this WP was to specify casters and steel grades which will be studied in this project as well as to provide cas ter an d cas ting p rocess d ata for t he partners for mod elling w ork. T he kn owledge of interrelations be tween c asting pa rameters a nd pr oduct qua lity i ncluding pr ocess s tability ha s be en summarised. Task 1.1 Specification of the casters of the industrial partners being investigated (all partners) In t his ta sk, c asters o f th e in dustrial partners were specified. Industrial p artners in t his project w ere DUFERCO, CAS and DUNAFERR. DUFERCO and CAS have b illet cas ters an d DUNAFERR vertical s lab cas ter. DUFERCO and DUNAFERR produce carbon s teels, CAS stainless s teels. Steel grades which were investigated in this project were determined and databases of caster machine data, operational p arameters an d cas ting p rocess p arameters wer e d elivered f or t he p artners f or m odel development. The investigated steel grades were:

• DUNAFERR: DD13, DD14, S235JRG2, S355J2G3C and St 52-3 • CAS: F304L1, 420A7 • DUFERCO: cold-headed s teel g rades ( mainly 20MnB4 a nd 3 0MnB4), pe ritectic C -

Mn-Ti steel C10C and high carbon grade C72D2 Industrial pa rtners de livered a ll t he d ata required f or modelling a nd o ther in vestigations; chemical compositions, material data, caster geometries and process parameters.

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Task 1.2 Summarising known interrelation between casting parameters and product quality as well as process stability (all partners) In general, al l t he p artners were f ocusing o n d etermining i nterrelations b etween cas ting p arameters, product qua lity a nd pr ocess s tability b ased o n c ommon k nowledge, results f rom f ormer p rojects, literature and discussions between the partners. As a result from the investigations BFI selected three critical variables which can be investigated with the BFI tools th at were the c ritical v elocity a t th e s teel m elt/liquid f lux in terface, th e liq uid f lux thickness and the wave height at the meniscus. CAS and CSM identified the main physical and geometrical parameters a ffecting the product quality which are related to the types of defects found. Both thermocouple data from CAS and solidification and shell stress modelling by CSM have been targeted at finding the conditions leading to undesirable shell growth. DUFERCO collected a table of influencing factors for the main surface defects on castings. AALTO collected k nown i nterrelations b etween p roduct q uality an d cas ting p arameters an d o f chemical compositions. Critical parameters and safety ranges defined in an earlier national project for fluid dynamics on optimising SEN, were presented shortly. DUNAFERR collected and evaluated the results from former R+D projects to determine the effect of casting parameters. They had modelled liquid pool depth and its shape and studied the effect of casting parameters on them. 1.2.2 WP2 SIMULATION OF MOULD POWDER BEHAVIOUR The m ain o bjective o f t his WP w as t o de velop m odels t o s tudy t he m ould po wder phe nomena responsible for bad casting quality and to determine important features and safety ranges for the quality control. DUNAFERR studies heat transfer phenomena of the strand. The partners in this WP are CSM, BFI and DUNAFERR. The models will be applied for industrial validations and testing in WP5. Task 2.1 Thermal transient model of powder heating and melting (CSM) CSM has simulated heating and melting of mould powder with its in-house “liquid pool model” model. A first version of t he m odel ha s be en e mployed t o de monstrate t he c apability o f c omputing s ome important features of the continuous casting process. Then, the following improvements for the model were made: a) a cal ibration stage and the first testing with the available pool height measurements; b) the introduction of a temperature-dependent sinterisation kinetic and of a density step-dependent on the void ratio to better represent the powder heating and melting dynamics. Task 2.2 Two-phase fluid-dynamics model of the steel/slag system (BFI) A n umerical m odel f or t he s teel/mould po wder system was d eveloped an d ad apted by BFI to ge t information o n th e velocity d istribution a t th e s teel m elt/liquid f lux in terface and th e th ree m ould powder layers (liquid flux, sintered, powder). Numerical computations were performed under variation of casting speed, immersion depths, l iquid flux film thickness and different material properties of the mould po wder, t o g ive de tailed i nformation o n v elocity di stribution, l iquid f lux t hickness a nd w ave height at t he m eniscus. The n umerical model was v alidated b y BFI with m easurement r esults f rom physical m odelling. The n umerical m odel was cap able t o co mpute t he t wo-phase f low an d t he entrapment o f dr oplets f or a no n-isothermal tw o-phase f low lik e th e s teel m elt/liquid f lux f low. The validation o f t he n umerical m odel f or t he i nterface d eveloped s howed good a greement of velocity

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distribution and wave formation in correlation to the measurements in the physical model. Numerical computations of the thermo-fluid flow show the liquid flux and sintered layer of the mould powder. Task 2.3 Fluid dynamics model of the flux infiltration (CSM) The ai m of CSM was t o investigate the o scillation mark formation a s r elated to th e f luid-dynamics arising in the liquid flux layer inside the mould-shell gap. Instead of the initial plan of developing a new model with the FEM code FLUX, an existing in-house developed code was upgraded. This new code provides a solution for the velocity and pressure fields inside the shell-to-mould gap, similarly to what was planned. As an improvement to the original plan, the model estimates the shape of the meniscus and s imulates t he f ormation o f t he o scillation m arks as a consequence. T his is v ery u seful to get understanding of the origin of defects connected to the lubrication problems in the mould. To make the model able to calculate the oscillation mark profile, a critical review of the hypotheses considered in the fluid-flow model of m ould f lux i nfiltration h as b een car ried out an d a f ew modifications h ave b een introduced. Task 2.4 Performance of supplementing physical model trials for provision of additional basic information as well as boundary conditions (BFI) BFI made physical model trials in a full-scale mould with two different measurement methods to get detailed information on the interface (water/oil) and velocity distribution:

• Flow vi sualisations wh ere u sed t o measure t he wav e h eight at t he i nterface and s how o il entrainment

• Particle i mage v elocimetry was u sed t o m easure t he f low velocities i nside t he wat er an d o il flow

From t he flow v isualisations the f ollowing things were o bserved: oil e ntrapment f or hi gher c asting speeds, SEN geometries with an exit angle directed more towards the interface, lower immersion depth of the SEN and thinner simulated mould flux films. With the PIV measurements the computed critical velocity of 0 .23 m/s for the water/oil combination was validated. Oi l en trainment was observed f rom BFI at lower velocities th an th e c ritical velocity d ue to th e highly tu rbulent f luctuations in th e f low. BFI observed t hat wave h eights increased at t he water/oil i nterface wi th an i ncreased cas ting s peed, decreased immersion depth and decreased SEN exit angle directed towards the interface. Task 2.5 Adaptation of DUNAFERR model for the qualification of the liquid pool depth and the shape (DUNAFERR) In order to characterise the t emperature field inside and on the surface of the s lab special evaluation system was developed by DUNAFERR and OBUDA for quantitative description of cooling effects and liquid pool shape. Parameters calculated by cooling curve evaluation software gave the possibility for quantitative c omparison o f d ifferent c asting te chnologies f rom th e p oint o f v iew o f s urface c ooling intensities. 1.2.3 WP3 SIMULATION OF FLUID FLOW AND SOLIDIFICATION BEHAVIOUR The m ain objective o f th is WP i s t o develop m odels t o s tudy t he f luid f low, t hermomechanical behaviour o f m ould a nd steel melt, as wel l as solidification p henomena a nd to d etermine im portant features and safety ranges for the quality control. The partners in this WP are CSM, BFI, DUNAFERR and AALTO. The models developed will be applied for calculation of industrial trials in WP 5. Task 3.1 Development of a steady-state 3D thermo-mechanical model of the mould (CSM) In this task CSM developed a steady-state 3D thermomechanical FEM model for the mould. Thermo-mechanical b ehaviour o f an el astic - perfectly p lastic t aper-less co pper m ould was s imulated. H eat transfer between t he mould with steel, cooling wat er an d ai r was t aken i nto ac count in c alculations. Proper geometrical, thermal and mechanical boundary conditions were used in the model.

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A s o-called “i nverse ap proach” was used t o g et h eat f lux an d t emperature m aps at l iquid-solid s teel interface s tarting f rom t he t hermocouple d ata obtained from the CAS caster (average h eat flux an d surface v elocity. These r esults were used a s i nput for bo th t he 3D m ould m odel a nd f or t he 2D solidification model in Task 3 .2. The displacement field results of both the mould and the steel allow the computation of the gap between steel and the mould. Task 3.2 Development of a transient 2D thermo-mechanical model of the solidification in the mould (CSM) Here CSM developed a t ransient 2D thermo-mechanical model for the mould area for calculation of solidification. Heat t ransfer an d s tress analysis were coupled, a nd t ime-dependent heat f lux pr ofile simulates travelling of the steel slice inside the mould. Elasto-plastic constitutive equation was used. A thermo-mechanical an alysis was performed t o as sess t he s tress-strain f ields d uring th e s olidification without the contribution of ferrostatic p ressure. The shell surface geometrical evolution was obtained from the computed displacement in the cross-section plane. Heat flux and temperature maps at liquid-solid steel for this 2D solidification model were obtained by “inverse approach” using the thermocouple data from CAS caster (as well as in Task 3.1) Task 3.3 Development of a steady-state 3D thermo-fluid-dynamics model of the strand (BFI) A s teady-state 3 D t hermo-fluid-dynamics n umerical m odel was d eveloped an d adapted by BFI. The developed numerical model was capable to get information on the temperature distribution inside the steel m elt, th e m ould f lux a nd in th e s olidified s hell, a s w ell a s th e v elocity distribution a long th e complete strand. Task 3.4 Adaptation and further development of the macrosegregation model (DUNAFERR) In t he f rame of f urther d evelopment of t he m acrosegregation m odel DUNAFERR and OBUDA implemented a new calculation method into its LMI model in order to take into account the deformation of solid shell during casting (LMI = Liquid Motion Intensity model). Besides the cooling effect, LMI model i s ab le t o t ake i nto co nsideration s everal i mportant f actors wh ich af fect t he f ormation o f centreline segregation (support roll position, eccentricity, bulging, etc.). Two critical parameters – the porosity a nd m ushy liquid r elative flow r ate – were i ntroduced f or ch aracterisation o f cen treline segregation level in the slab. Task 3.5 Adaptation and further development of the columnar to equiaxed transition model (DUNAFERR) In th is ta sk DUNAFERR and OBUDA developed and a pplied a n umerical m odel t o estimate t he columnar to equiaxed transition (CET) under industrial circumstances. A set of industrial castings was analysed by heat t ransfer model in order to determine the thermal conditions ahead the liquidus front when transition happens. As a result, empirical model for predicting the columnar to equiaxed transition was developed. Task 3.6 Solidification model (AALTO) In this task the solidification model intended to be developed further was changed (CDG to IDS). AALTO developed further and improved IDS solidification model by making a broad literature search and utilising t he e xperimental da ta f ound. T he e xtension a nd/or i mprovement o f G ibbs’ e nergy databanks has been performed by assessing a large amount of ternary phase system data of steels. Also experimental data on formation of new complex inclusions and precipitations have been assessed to the model. Large m aterial p roperty d ata s et h ave b een co llected an d as sessed to IDS. As a r esult o f th e development w ork, composition r anges have be en w idened e nabling t he s olidification s imulation of new s teel grades. In addition formation of new inclusions and precipitations has been assessed to the model.

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Task 3.7 Adaptation of the DUNAFERR model for the prediction of the temperature evolution in the strand and prediction of surface and inner cracks formation (DUNAFERR) In th is ta sk DUNAFERR analysed an d ad apted S chwerdtfeger’s m ethod f or cal culation o f “accumulated damage” in the surface area of s labs for the casting conditions at DUNAFERR. Model for cal culation of “a ccumulated d amage” f unction h as b een d eveloped. According t o t his t heory t he repetition of c reeping processes caused by c yclic cooling (at cooling nozzles) and reheating (between nozzles) decreases the ductility resulting in surface cracks. As a reference the ductility of base material (without “accumulated damage”) can be used (ductility trough curves as a function of temperature and strain rate). 1.2.4 WP4 SIMULATION OF PHASE TRANSFORMATION The main objective was to d evelop a n on-line m odel describing the phenomena of heat t ransfer and phase transformation along the strand including IDS solidification and microstructure model from WP3. This co upled m odel p ackage wi ll b e u sed t o d etermine i mportant f eatures an d safety r anges f or t he quality control. Task 4.1 Development of the 3D heat transfer and phase transformation model (AALTO) In this task AALTO developed further and improved its in-house heat transfer models; the dynamic 3D on-line simulator, C astManager, a nd 3D steady-state model, T empsimu w hich i s ne eded f or t he simulations with dynamic model. Boundary condition options of Tempsimu have been enhanced. Also semi-empirical austenite d ecomposition m odel ADC has be en i mproved. A g reat amount of C CT diagrams have b een d igitised i n n umerical f orm an d i ts r elated data, steel c omposition, a ustenitising temperature, austenitising tim e and g rain s ize have been m odelled with s tatistical m ethods. This development wi dens t he s teel co mposition r anges an d i mproves t he accu racy of cal culating p hase transformations. On-line casting simulator consists of CastManager, (Tempsimu), ADC and IDS (Task 3.6) models and casting process data. This simulator calculates temperatures and isotherms in the cast strand three-dimensionally in d ynamic casting conditions. In addition CastManager was coupled wi th IDS and ADC enabling the on-line calculation of phases, and phase fractions all along the strand during a real industrial cast. 1.2.5 WP5 MODEL APPLICATION AND VALIDATION IN STEADY-STATE CONDITION The objective of this work package was to produce experimental data from casting trials and to use the models developed i n WP2, WP3, WP 4 to s imulate c asting c onditions c orresponding to th ese tr ials. Also calibration of the models and definition of safety ranges for the critical features defined in other work packages will be performed. Task 5.1 Adaptation of caster plants (DUFERCO, CAS, DUNAFERR) Caster moulds of CAS were machined and instrumented to perform experimental trials on 160*160mm2 square b illet cas ting. T he t hermocouple ar rangement was set i n o rder t o ha ve i nformation o n t he occurrence of uneven heat transfer between shell and mould along the perimeter and along the distance from the meniscus up to the heat flux between shell and mould. Four moulds wer e co ated wi th n ickel an d eq uipped wi th t hermocouples t o m easure t emperature distribution during the casting process at DUNAFERR. A new line-scanner was put into operation to measure the surface temperature of the s trand. Temperature distribution of the moulds during casting and s trand s urface t emperatures were o btained for further ev aluation. H eat flux in the mould can be calculated. These results were used in WP5 for calibration and validation of DUNAFERR model.

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Surface le vel in spection s ystem w as in stalled in DUFERCO within th e f rame o f th is p roject. In addition, n ew au tomatic p owder f eeding s ystem was i nstalled. Os cillator h as been ch ecked a nd r e-aligned. Task 5.2 Execution of cast trials, data acquisition and sample collection for microstructural analyses (CAS, DUFERCO, DUNAFERR) In this task cast trials were performed at the steel plants of CAS, DUFERCO and DUNAFERR. At CAS cast trials were performed with the instrumented mould. A reasonable thermal field has been measured. Sample collection has been carried out both on as-cast billets and on rolled products to assess the presence of defects. The ghost line defect class was investigated. Castings experiments were carried out a t DUNAFERR to investigate the effect of casting parameters on the microstructure and surface quality of the slabs. Centreline segregation properties were evaluated by means of Baumann prints and macro-etched samples of the s labs. Database of c asting parameters and co llected s amples ar e a vailable f or f urther e valuation. These r esults wer e u sed i n W P5 f or calibration of DUNAFERR model. DUFERCO made casting trials on its billet caster and it can be concluded that with the crack sensitive grades decreasing the water flow rates from the previous values in secondary cooling, the quality of the billets was improved. The hot ductility of the steel was better at the unbending point which resulted in less corner cracks in the billets. The improved quality could also be seen in the lower rejection rates of wire rods. Task 5.3 Execution of microstructural analyses (DUNAFERR, CSM) Scanning Electron Microscope observation and Energy Dispersive X-ray analysis were made at CSM on previously etched billet p ieces of CAS. Elements characterising the casting powder were found in the macro-inclusion agglomerates. The tendency of the austenitic steel F304L1 to be prone to powder sticking has been confirmed. The occurrence of such a d efect has been correlated to improper powder melting at start of casting. Improved powder compositions were suggested in order to favour the rapid formation of a reliable liquid pool. Microstructures of t he s labs were evaluated af ter casting trials at DUNAFERR. Several et ching methods wer e t ested t o r eveal microstructure an d m acrosegregation. As a r esult, t he b est et ching methods were selected. The r elationship b etween cas ting p arameters an d m icrostructure i s m ore understood. These results were used in WP5 for calibration and validation of DUNAFERR model. Task 5.4 Calibration of the models (BFI, CSM, DUNAFERR, AALTO) The c alibration of t he num erical models de veloped i n WP2 a nd W P3 w as und ertaken b y BFI with adapting the b oundary condition for t he n umerical computations and validated with t emperature d ata from DUNAFERR collected i n WP1. Results c omputed w ith th e n umerical models s how a good agreement wi th p rocess d ata. T emperature d ata an d s hell t hickness were captured wel l wi th t he numerical models. CSM calibrated the “liquid pool model” deriving the parameter a of the sinterisation kinetic from the powder m elting r ate, a measurable p roperty of t he p owder: t he m elting r ate h as b een f ound experimentally b y m easuring the t ime n eeded of a powder l ayer t o melt dur ing a 1400°C solenoidal electromagnetic induction; then, this value has been used to recursively calibrate the model by a set of FEM s imulations. The h eat f lux p rofile ev olution f or each h eating h as b een c alibrated t o m ake t he corresponding t emperature f ield co nverge t o t he m easured d ata at m idface an d at t he corner. T he temperature f ield r esulting f rom 3 D t hermo-mechanical FEM s imulations o f the m ould h as been compared to the experimental data at corner and mid-face regions. A good agreement has been found

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about both the heats of the steels considered. The heat flux profiles producing such thermal fields have been employed as input for computing the mechanical evolution of the mould itself. DUNAFERR performed and analysed casting trials and in all cases OBUDA performed solidification, heat transfer and centreline segregation modelling. Gleeble measurements were used for calibration of creep models. In order to calibrate and validate the model, six trials under well-defined parameters were performed by Gleeble 3800 type thermo-mechanical simulator at College of Dunaujvaros. The Gleeble 3800 g ives t he p ossibility t o p erform c reep t ests as s train o r s tress co ntrolled p rocesses. C entreline segregation model was calibrated by means of metallographical examination of cast products (Baumann prints, macroetched samples). IDS model h as previously been v alidated wi th t he r esults o f m any ex periments f rom l iterature performed wi th s teel g rades o f wi de compositional r anges. H eat t ransfer b oundary co nditions i n Tempsimu and in CastManager models have been validated with experimental heat transfer coefficients of water and air-mist nozzles, rolls and air convection. Models and data needed for the on-line simulator CastManager were set up and testing simulations were made with a whole package by AALTO. Task 5.5 Definition of safety ranges (BFI, CSM, DUNAFERR, AALTO) Critical surface velocity values that result to be risky for some defects occurrence have been identified by CSM: h igher values at meniscus ease the s lag-steel emulsification, while at hot spot they ease the shell ‘washing’, up to break-out risks. Relationships between segregation index and equiaxed zone are derived from literature. The gap profile determines a reduction in heat flux going from the midface to the c orner, r esulting i n p henomena t hat c onstitute a w arning f or p otential d efects, th en a c ritical parameter h as b een i dentified i n the h eat f lux p rofile d erived f rom t he t emperatures measured i n the mould. Set of calculations were performed by DUNAFERR and OBUDA and the result were evaluated in the light of experiences of industrial trials. Two critical parameters were identified: The porosity level and mushy liquid relative flow rate as critical parameters can be taken into account as characteristic features of centreline segregation. DUFERCO defined f or c ritical variables Ferrite p otential a nd C opper E quivalent, f ormulas w hich describe cracking sensitivity calculated from steel composition. IDS an d ADC m odel based quality i ndices wer e introduced by AALTO. Quality i ndices (values between 0 an d 1 , 0 =excellent q uality, 1=poor q uality) are d ivided in to s olidification r elated and austenite decomposition related indices. The developed indices are the following: QISTR=strengthening problems in mushy zone, QISOL=ductility drop close to solidus temperature, QISHE=disturbance of shell growth close to solidus temperature, QIGRA=ductility drop induced by large grain size, QICOM=ductility drop i nduced by i ncreased pr ecipitation g rowth, QIADC=ductility d rop in s tart of a ustenite decomposition, QIHAR=hard final structure. BFI determined cr itical parameters at DUNAFERR caster f rom its f luid-flow s imulations. T he parameters were velocity at the interface steel melt/ liquid flux interface, wave height of the interface and liquid flux thickness. The safety ranges for the critical variables are:

• A maximum critical velocity at the steel melt/liquid flux interface of approx. 0.39 m/s for the selected steel grade and mould powder materials data was defined.

• A minimum flux thickness was defined to 8-10 mm from the investigations. • A maximum wave height of 15-20 mm was defined.

Task 5.6 Execution of calculations with all the provided data and tuning of the safety ranges (BFI, CSM, DUNAFERR, AALTO) Numerical c omputations were u ndertaken b y BFI for a ll t he provided da ta f rom DUNAFERR for a number o f d ifferent p rocess p arameters which were casting s peed, i mmersion d epth o f S EN, S EN geometry and mould powder thickness. Flow and temperature fields for all the investigated parameters

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were o btained. The r esults o f th ese c omputations w ill b e u sed in W P6 to d evelop th e interrelations between critical variables and casting parameters for the use in an on-line model. CSM calculated the casting trials of CAS with its 3D mould and 2D steel simulation models. 3D mould: the top of the mould is usually constrained by the flange; the mould body enlarges about 0.1mm al ong al l i ts b ody ap art i ts f ree end, wh ere t he en largement i s m aximum an d eq ual t o ab out 0.2mm in both the heats considered. 2D steel: the formation of the hot spot in the off-corner region is clearly shown; at the mould exit, the steel shell is detached from the mould all around the perimeter. This occurs also because of the absence of ferrostatic p ressure i n t he model; t he max d etachment i s f ound a t t he corners (about 0.8mm); the shrinkage of the steel CAS 420A7 is higher than the one of steel CAS F304L1. A hot-tearing index has been i mplemented i n t he FEM co mmercial co de b y a u ser s ubroutine t o s tudy t he ghost lin e defect class: at the mould exit, the computed non-zero h ot-tearing r egions in s teel CAS 420A7 are g lobally wider than in steel CAS F304L1. The computed gap is not always coherent with the heat flux evolution during casting because of a different stratification of the solid slag layers due to the different thermo-physical p roperties o f t he l ubricating p owders u sed f or cas ting t he s teels i nvestigated. On e o f t he thermo-physical properties that can affect the heat transfer is the basicity index: the higher the basicity index the lower the heat transfer. A number of 41 casting trials were performed at DUNAFERR. During the trials special attention was paid for the roll setting accuracy and – partly as a result of the tests – the roll setting concept has been changed. The LMI model parameters were calculated both for the original and for the modified setting of cas ter rolls ( roll t aper). It can b e co ncluded t hat i n 9 5 % o f cas ting cas es t he cal culated an d qualitatively evaluated levels of centreline segregation (characterised by porosity and relative flow rate fuctions) in the slab were in good accordance. AALTO simulated solidification a nd he at t ransfer i n t he s trand i n casting tr ials o f DUFERCO and CAS. DUFERCO and CAS classified heats to be simulated with good and bad quality and intension was to study whether there were differences between these steel groups which could explain the quality. (Results in Final Summary Task 6.2). 1.2.6 WP6 DEVELOPMENT AND APPLICATION OF THE EMPIRIC ON-LINE MODEL OPTIMISED FOR PROCESS CONTROL Objectives in this Work Package was to find out empirical relationships between critical parameters and safety ranges as obtained from the casting trials and developed models in order to use them in the on-line casting simulator. As a consequence, the objective is to elaborate the guidelines for the extension of the new on-line model for detecting and controlling the casting process in other continuous casters. Task 6.1 Formulation of empirical relationships between the critical variables and input sets of input parameters (all partners) Interrelations were formulated by BFI for critical parameters for all the investigated process parameters such a s the i mmersion de pth o f t he S EN a nd m ould po wder t hickness. From t he n umerical computations BFI developed interrelations are available for the critical parameters (critical velocity at the interface, liquid flux thickness and wave height) for the use in the on-line model. On the basis of the mechanism leading to the application of tensile stresses on the solidification front, CSM determined an em pirical r elationship b etween t he cr itical v ariable i dentified ( the h eat f lux difference between the midface and the corner) and the process parameters. In these terms, a possible route t owards a p rocess r egularisation c ould i nvolve t he upda ting o f t he c asting s peed, t he c asting powder and the mould taper. DUNAFERR and OBUDA designed and prepared a special database which consists of pre-calculated data o f 2 2 cas ting cas es. T hese cas ting cas es co ntains b oth s teady-state and n on s teady-state tim e periods. Casting cas e an alyser s oftware was d eveloped f or s tudying an d d isplaying t he cal culation

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results collected in the database. The use of developed database and software gives the possibility to perform individual analysis of each casting case. The critical variables: the expected porosity level and the s everity o f t he r elative mushy l iquid f low l evel can b e p redicted. There i s a complex connection between cr itical p arameters an d i nput data, s o empirical r elationship b etween critical p arameters an d input data cannot be easily defined. Task 6.2 Estimation of the limits for the variable changes inside which a regular casting process is guaranteed (all partners) Three on-line models were developed in this project: Two of them, CastManager (AALTO) and LMI models (DUNAFERR and OBUDA) are dynamic heat transfer model of the whole strand and they are capable for controlling cast in real time. CastManager and LMI model are universal for all the casting sizes b ut LMI model is e specially s uitable f or s lab c asting in cluding th e e ffect o f r oller s ettings, eccentricies o f s upporting r olls, bul ging a nd shrinkage, t he issues which ar e i mportant i n t erms o f centreline s egregation and i nner qua lity in s labs. CastManager was co upled i n this p roject wi th IDS solidification and ADC austenite decomposition models. Thus CastManager now calculates phases and phase fractions all along the cast strand on-line during real industrial casting. CSM developed an inverse on-line model for calculating heat flux difference between the midface and the corner of the billet from the mould temperature measurements. Heat flux could be computed on-line submitting th e lo gged te mperature p rofiles a long th e th ermocouple lin es t o a thermal c omputation iteratively till th e computed thermal field fits the measured field. In principle this could be coupled to CastManager model which has a s eparate mould heat t ransfer calculation model and uses now earlier defined h-gap curve. Critical values for CAS steels for bo th the surface velocity and t he h eat f lux d ifference b etween t he midface and the corner have been identified by CSM: 0.30-0.35m/s and 0.30MW/m2. The critical value 0.30MW/m2 has been confirmed using available set of data of a third steel grade selected as reference for a critical internal defect situation. Safety ranges for critical parameters: the critical velocity, the liquid flux thickness and the wave height from numerical fluid flow computations were defined as a function of casting parameters by BFI. These values are used as initial limit values for casting at DUNAFERR for the LMI on-line model with the steel grade being cast. DUNAFERR analysed more than 40 casting cases from this point of view. In the half of cases beyond the d ataset o f t echnological p arameters an d m odelling r esults t he s ulphur p rint an d m acroetching photographs of the s labs were al so available. The calculation results p roved that in order to keep the critical variables in the safety range the complex treatment of input parameters (casting parameters and conditions) and the individual analysis of casting cases is necessary. DUFERCO estimated l imits f or cr itical i ssues wh ich t hey h ave e xperienced t o h ave i nfluence o n quality of certain steels. (Task 5.2.) AALTO simulated heats of DUFERCO and CAS, which were classified into good and bad quality. IDS cal culations s howed t hat d uring s olidification o f b oth CAS and DUFERCO steels Nb(C,N), V(C,N) and AlN precipitations can form which increases the cracking risk. Those compounds start to form between 700-1000°C depending on steel composition. Thus it is important to control cooling so that formation o f t hese e lements c ould be di minished. Heat tr ansfer s imulations showed very small differences in s urface t emperatures wi th good a nd ba d qua lity he ats. Anyway, t he ab solute co rner temperatures changed fast after the mould and dropped down to 800°C. So according to the simulations a softer cooling could be tested after the mould exit. DUFERCO had good results on steel quality when they decreased secondary cooling with their crack sensitive steel grades. Steel grade 420A7 of CAS had problems wi th subsurface cracks and the average d istance of crack f rom the b illet surface was 14-15 mm. According to the heat transfer simulation and theory behind crack formation the place at the caster where the cr acks had been formed was around 1 m f rom meniscus, w hich is just th e location where surface temperatures drop rapidly to rise again, which increases the thermal stresses.

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Task 6.3 Elaboration of guidelines for the extension of the new on-line model for detection and controlling the casting process to other continuous casting machines (all partners) The results elaborated by BFI in WP5 were used to elaborate general guidelines for continuous casters. An opposite behaviour for the optimization of the fluid flow and the heat transfer can be observed from results. I t was s een f rom t he i nvestigations t hat p arameters, r esponsible f or a good be haviour of t he fluid flow are not good for the thermal behaviour of the casting powder. For example a decrease of the immersion depth will lead to smaller flow velocities at the steel melt/liquid flux interface and reduce the risk of liquid flux entrapment. But reducing the immersion depth will also reduce the heat transported to the casting powder and therefore can reduce the liquid flux thickness. After measuring and s toring instantaneous data from process, CSM proposes a h ypothetical heat f lux profile as input to the thermal computation. From the heat flux profile, the temperature at each quota and the corresponding relative gap with the acquired thermal profile are computed to update the heat flux profile for a further thermal computation step if that gap does not fit the chosen tolerance criterion.

The LM I o n-line model of DUNAFERR and OBUDA can be adapted to s imulate o ther s lab cas ting machines. The validity of the relationships built in LMI model are independent on the individual casting machine design. The precise set of input data is necessary for application of LMI model (caster machine data, primary and secondary cooling, technological parameters, etc.). Special attention has to be paid for precise measurement of actual setting of supporting rolls (measurement by roll checker device). because centreline s egregation i s b asically affected, at a given c omposition an d co oling t echnology, b y t he setting of the supporting rolls, by the accuracy of the strand (e.g. adjustment accuracy of the supporting rolls), by the rigidity of the supporting rolls as well as by the shape distortion of the supporting rolls (eccentricity or we ar). Bulging of t he s trand b etween t he s upporting rolls can a lso p lay role, s o t hat reliable model for bulging calculation (like BOS connected to TEMPSIMU) is also necessary. The CastManager on-line model of AALTO can be adapted to other casters, as well. First the caster has to be s et up i n t he T empsimu s teady-state m odel, r equiring data o f caster geometry, cooling z ones, location of n ozzles an d r olls an d water in tensities through t he no zzles on t he s trand s urface. For CastManager p rocess d ata; cas ting s peed, co oling wat ers et c. a re n eeded. When us ed a s a n o n-line model the process data has to come automatically in the defined form to the model from the automation system of the caster. CastManager can be used off-line too, as a tool for studying the different casting cases and casting parameter changes. From IDS and ADC models solidification, phase transformation, inclusions and p recipitations a re obtained. Through c oupling IDS and ADC t o t he CastManager, t he model cal culates p hases f ormed an d p hase fractions on -line d uring c asting. Quality i ndices can b e calculated wi th IDS (combined with ADC) model, but the indices are not yet d irectly c oupled to the model. This i s pl anned t o be do ne in t he ne ar f uture. Then the m odel w ill a ble to show on -line th e appearance o f t he quality r isks dur ing real cas ting. These q uality i ndices ar e n ow u sed o ff-line determining the quality of the steel.

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2 SCIENTIFIC AND TECHNICAL DESCRIPTION OF RESULTS 2.1 Objectives of the project The main objective of the project is to develop a new modelling based optimisation and quality control system for continuous casting which could also be applied as an on-line control during casting. The new concept wi ll b e b ased o n f inding p arameters an d f eatures wh ich ar e cr itical f or s teel q uality from casting experiments an d mathematical models an d d etermine s afety ranges f or t he p arameters wi thin which good steel quality is ensured. Objectives of the Work Packages were the following: WP 1 Definition of reference casting condition Objective of this WP was to specify casters and steel grades which will be studied in this project as well as t o p rovide cas ter an d cas ting p rocess d ata for t he partners for modelling work. The knowledge o f interrelations b etween cas ting p arameters an d p roduct qua lity i ncluding pr ocess s tability ha s be en summarised. WP 2 Simulation of mould powder behaviour The m ain o bjective of t his WP w as t o develop m odels t o s tudy t he m ould pow der phe nomena bad casting q uality and t o de termine i mportant f eatures a nd safety ranges f or t he q uality co ntrol. DUNAFERR studies heat t ransfer phenomena of the s trand. The partners in this WP are CSM, BFI and DUNAFERR. The models will be applied for industrial validations and testing in WP5. WP 3 Simulation of fluid flow and solidification behaviour The m ain objective o f th is WP is t o develop m odels to s tudy th e f luid f low, th ermomechanical behaviour o f m ould an d steel m elt, as wel l as s olidification p henomena an d t o d etermine i mportant features and safety ranges for the quality control. The partners in this WP are CSM, BFI, DUNAFERR and AALTO. The models developed will be applied for calculation of industrial trials in WP 5. WP 4 Simulation of phase transformation The main objective was t o d evelop an on-line m odel describing the phenomena of heat transfer a nd phase transformation along the strand including IDS solidification and microstructure model from WP3. This co upled m odel p ackage wi ll b e u sed t o d etermine i mportant f eatures an d safety r anges f or t he quality control in WP5 and WP6. WP 5 Model application and validation The objective of this work package was to produce experimental data from casting trials and to use the models de veloped i n W P2, WP3, W P4 t o s imulate c asting c onditions c orresponding t o t hese t rials. Also calibration of the models and definition of safety ranges for the critical features defined in other work packages will be performed. WP 6 Development and application of the empiric on-line model optimised for process control Objectives in this Work Package was to find out empirical relationships between critical parameters and safety ranges as obtained from the casting trials and developed models in order to use them in the on-line casting simulator. As a consequence, the objective is to elaborate the guidelines for the extension of the new on-line model for detecting and controlling the casting process in other continuous casters.

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2.2 Comparison of initially planned activities and work accomplished DUNAFERR did no t pl an a daptation of c aster m oulds, but i n July 2007 t he E uropean C ommission confirmed that it is possible to transfer costs from the raw material category of other operating costs to the cat egory en titled as " alteration an d t ransformation o f ex isting e quipment". B ased o n t his confirmation DUNAFERR equipped two moulds with thermocouples. Otherwise the project proceeded according to the initial plans. 2.3 Description of activities and discussion

2.3.1 WP1 DEFINITION OF REFERENCE CASTING CONDITIONS Objective of this WP was to specify casters and steel grades which will be studied in this project as well as t o p rovide cas ter an d cas ting p rocess d ata for t he partners for modelling work. The knowledge o f interrelations be tween c asting pa rameters a nd pr oduct qua lity i ncluding pr ocess s tability ha s be en summarised. Task 1.1 Specification of the casters of the industrial partners being investigated (all partners) In this task casters and steel grades in this project were specified. DUNAFERR produces carbon steels and has two vertical slab casters of which both are used in this project. The moulds of the casters are adjustable within sizes 860-1550*240 mm. CAS produces stainless steels with a four line billet caster, mould size being 160*160 mm2. DUFERCO produces carbon steel billets of size 143*143 mm² with a continuous caster of six lines. The following steels of CAS have been investigated in the project by considering the types of defects of interest and the model capabilities: CAS 420A 7 - martensitic p eritectic r esulphurised steel s ubject to lo ngitudinal c racks a nd

depressions and with excessive depth of the oscillation marks

CAS F 304L1 - austenitic l ow ca rbon r esulphurised s teel s ubject t o en trapment o f t he non-melted casting powder and consequent re-carburisation of the billet surface

The chemical compositions of the steels are in Table 1-1.

Table 1-1. Chemical compositions of the CAS reference steels.

Steel grade Chemical composition [wt %]

C S P Si Mn Cr Ni N CAS F304L1 0.02 0.023 0.04 0.20 1.25 18 10 0.045 CAS 420A7 0.20 0.025 0.03 0.40 0.50 13 - -

CAS has collected and delivered liquid pool height and mould temperature data to CSM. The practice of powder addition has been moreover observed for achieving data needed for modelling the powder melting process.

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DUNAFERR provided cas ter and p rocess data to i ts subcontractor OBUDA for modelling purposes. The investigated steel grades of DUNAFERR and their compositions are shown in Table 1-2.

Table 1-2. Typical chemical compositions of steels produced at DUNAFERR.

Heat No. Grade weight% C Mn Si S P Al Ti V Nb

532066 DD13 0.041 0.21 0.009 0.012 0.0063 0.031 ≤0.0010 ≤0.0010 ≤0.0010 628886 DD14 0.043 0.20 0.009 0.009 0.0070 0.036 0.022 0.0020 0.0040

534637 S235JRG2 0.11 0.62 0.011 0.012 0.0097 0.052 ≤0.0010 0.0012 ≤0.0010

637103 S355J2G3C 0.17 1.39 0.20 0.007 0.011 0.047 0.0013 0.0028 ≤0.0010

637358 St 52-3 0.17 1.45 0.32 0.005 0.011 0.060 0.0015 0.0034 0.0020 DUFERCO focused in this project on cold heading grades, mainly 20MnB4 and 30MnB4. In addition, peritectic C-Mn-Ti steel C10C and high carbon steel, C72D2 were studied (Table 1-3.)

Table 1-3. Chemical compositions of the steel grades DUFERCO in this project.

DUFERCO and CAS provided n ecessary d ata f or modelling t o AALTO. T he models a pplied were heat t ransfer an d s olidification m odels and t he data n eeded were: s teel co mpositions, cas ter d esign, casting p arameters an d es pecially t he a ccurate d ata f or s econdary cooling (locations o f t he n ozzles, rolls, w ater d istribution o f t he n ozzles, et c.). Also r eal p rocess d ata o f t he ca sts wer e d elivered t o AALTO for dynamic heat transfer calculations. The work at BFI was concentrated on the casting of flat products. Here the operational situation of the slab caster from DUNAFERR was considered. DUNAFERR delivered the boundary conditions from to B FI to g enerate a s et of r elevant d ata t o p rovide a d ata b ase f or t he p hysical s imulations an d numerical co mputations. T hose we re t he g eometry d ata ( SEN, cas ter l ength, mould s ize, l ength of primary an d s econdary c ooling zone) p rocess p arameters ( inlet mass f low, i mmersion d epth) and the thermal boundary conditions (inlet melt temperature, cooling rate in the mould, cooling conditions for the s econdary co oling zo ne, s hrinkage o f t he s trand). T he different S EN g eometries i nvestigated ar e shown i n Figure A -1 (Appendix) and a selection o f co llected d ata was s ummarised i n T able A-1 (Appendix). Additionally a s teel g rade f or the in vestigations w as s elected and th e m aterial p roperties of th is particular steel grade S460ML (1.8838) were computed, Table A-2 (Appendix). The material data for a common mould powder was received from DUNAFERR and not otherwise specified material data was taken f rom l iterature. With t he as sembled p rocess p arameters b oundary co nditions f or t he p hysical simulations and the numerical computations were appointed.

Ste

el

Gra

de

Gra

de

%C

%M

n

%S

%P

%S

i

%C

u

%A

l

%N

i

%C

r

%M

o

%N

2

%B

%Ti

Ceq

Cue

q

FP

A 20MnB4 0,203 1,057 0,004 0,013 0,216 0,064 0,035 0,042 0,054 0,010 0,0090 0,0030 0,030 0,400 0,069 0,753A 30MnB4 0,297 0,852 0,006 0,012 0,087 0,061 0,038 0,045 0,210 0,009 0,0080 0,0030 0,036 0,491 0,073 0,514A 19MnB4 0,206 0,917 0,007 0,012 0,038 0,064 0,039 0,046 0,058 0,008 0,0080 0,0030 0,031 0,380 0,078 0,716A 23MnB4 0,216 0,945 0,006 0,012 0,056 0,058 0,034 0,041 0,262 0,008 0,0080 0,0030 0,034 0,435 0,061 0,711B C10C 0,092 0,410 0,006 0,012 0,034 0,064 0,035 0,045 0,054 0,007 0,0080 0,0000 0,016 0,180 0,091 1,022C C72D2 0,727 0,547 0,012 0,011 0,188 0,059 0,003 0,046 0,052 0,007 0,0070 0,0000 0,001 0,837 0,053 -0,524

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Task 1.2 Summarising known interrelation between casting parameters and product quality as well as process stability (all partners) BFI concentrated on physical and numerical investigation of the fluid flow phenomena responsible for defects and the liquid flux behaviour along the meniscus and over casting pool. Both parameters fluid flow an d liquid f lux be haviour a re i nfluencing pr oduct q uality a nd t he e ntire s tability of t he c asting process. Many cas ting d efects were related t o t he f luid f low i nside t he s lab cas ter m ould. S teel m elt f low velocities and turbulence can have a significant effect on surface quality and process control problems [1]. The “ double r oll” f low p attern, lik e it is d eveloped w ith th e SE N u sed b y DUNAFERR, was considered t o b e t he m ost s atisfactory f or s uccessful cas ting. T urbulence ca uses t he f ormation of standing wav es at th e s teel melt/liquid f lux in terface. Liquid m ould f lux w as entrained due t o hi gh velocities, vortexing or highly unsteady flow conditions that shears liquid flux from the interface, [2]. The formation of waves at the interface in combination with a thin mould powder layer can lead to a considerable r eduction o f l iquid f lux t hickness a nd a n i nsufficient l ubrication due t o a r educed infiltration of liquid f lux [3]. Liquid f lux en trainment defects were al so related to SEN geometry in combination with turbulence induced at the interface steel melt/liquid flux [4]. There were a variety of s urface d efects, wh ich were t raced t o the m ould powder used in the casting process. Of these, four in particular were directly affected by the mould powder used, that were surface defects from entrapped liquid flux, longitudinal cracks, corner cracks and oscillation marks [5]. Mould level fluctuations had an influence on crack formation, especially on corner cracks in casting low and ultra-low carbon s teels [6]. A thicker interfacial l iquid flux layer was associated with a h igher rate of flux infiltration into the gap [7-9]. They observed that a number of defects in steel slabs were reduced with a s ufficiently th ick liq uid f lux la yer a bove th e melt p ool. This p rovided better lu brication a nd lowered heat f lux. I t al so i mproved h eat f lux u niformity, wh ich d ecreased s urface d efects [10,11] A non-uniform heat f lux di stribution inside the mould l ed to corner c racks and longitudinal c racks [1]. Very often the temperature distribution was also correlated to the mould lubrication which was strongly influenced by the mould powder behaviour. For slab casters the liquid flux thickness was measured in former RFCS-project by BFI and different partners [12]. The flow of liquid flux into the interfacial gap between the strand and the mould walls was important for productivity and quality in continuous casted slabs. Therefore liquid flux layer thickness will have a major influence on the product quality. Many process fluid flow parameters can have an influence on the liq uid f lux la yer th ickness lik e: c asting s peed, m ould le vel ( immersion d epth o f SE N), S EN geometry, melt temperature, fluid-dynamics in steel and liquid flux as well as mould powder properties. From all th e lite rature a m inimum liq uid f lux t hickness o f a t le ast 8-10 m m w as a ssumed t o be necessary. Liquid flux measurements with nail boards showed typically a liquid flux thickness of 13-20 mm for s lab cas ter m easurements. T he m aximum accep table wa ve h eights a t t he m eniscus wer e reported with 15-20 mm. When entrainment from the s teel melt/liquid flux interface occurs, relations can be given based on the Kevin-Helmholz equation to compute a critical velocity [13]. For the selected steel g rade f rom DUNAFERR for t he BFI investigation t he cr itical v elocity b ecame 0 .39 m /s. T he influences of the above stated relevant parameters on the fluid flow and the liquid flux thickness in the mould were analysed from BFI in its investigations for a continuous slab caster. Casting parameters CSM has identified the main physical and geometrical parameters affecting the product quality:

a. Height of the liquid slag pool on the meniscus, depending on: powder properties fluid-dynamics in the mould and at the steel-to-slag interface

b. Infiltrated liquid slag pressure in the gap, which depends mainly on the powder properties c. Mould gap thickness which depends on many process parameters and on the s teel properties,

the shrinkage behaviour near the meniscus is the most relevant. These parameters appear to be related to the presence of defects as follows:

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a. Height of the liquid slag pool on the meniscus can be related to the re-carburisation of the billet surface: small liquid pool heights could induce contact of non-melted powder with the shell.

b. Infiltrated liquid slag pressure in the gap can be related to sticking-type defects: if the pressure inside the mould/shell gap is too small, the lubricating slag film could break and the steel could stick to mould.

c. Gap thickness can be related to the occurrence of longitudinal cracks and depressions: in case of a too large mould-steel gap, the mould-shell heat transfer can be uneven, leading to hot spots occurrence and, in turn, longitudinal depressions and cracks.

The above detailed features have been investigated by the following CSM models:

a. Height of the liquid slag pool on the meniscus by “Liquid pool model” (Task 2.1); b. Infiltrated liquid slag pressure in the gap by the “Flux infiltration model” (Task 2.2); c. Gap thickness by the “Solidification model” (WP 3).

Product quality The f ollowing d rawbacks, r elated t o p roduct q uality as pect an d o perating p arameters, h ave b een identified by CAS: Powder e ntrapment ( focus o n F304L1 s teel) be cause o f ba d lubricating behaviour a t s tart of

casting. Here, one can ad equately modify t he p owder composition, r esponsible o f c hemical-physical behaviour during slag melting and gap filling

Surface crack formation caused by to too deep oscillation marks Re-carburisation i n co rrespondence o f d eep o scillation m arks. It c an b e r elated t o s lag

entrapment occurrence due to the rapid mould level variation. Internal cr acks ( ghost-lines) d ue to δ-γ transformation at s olidus t emperature. For t his as pect

related t o s teel co mposition, C AS h as ch ecked t he p ossibility of increasing the r ange o f temperature wh ere δ-ferrite is s table, i n o rder t o i ncrease s hell t hickness an d i n t urn ach ieve higher resistance to withstand the volume shrinkage.

As f ar as t he CAS steels u nder i nvestigation ar e co ncerned, t he m ain i nterrelation co ncerning s teel quality a nd pr ocess pa rameters relates t he t hermal d istribution t o t he s urface d efects ( cracks) occurrence. Then both CAS thermocouple data and CSM modelling concerning solidification and shell stress have been targeted at finding the conditions leading to undesirable shell growth. The f inite el ement an alysis d eveloped by CSM in t he WP3 a nd t he CAS observations a bout t he solidification phenomenology in the WP5 have al lowed t o define the interrelation between the set of casting p arameters i nfluencing t he m ould-shell co ntact an d the fo rmation o f o ff-corner s ub-surface cracks. The mentioned casting parameters are: Casting speed Steel composition

The mainly influencing geometry parameters are: Mould taper Corner radius

For a given mould taper and casting speed, the shrinkage of some steels can give rise to: Detachment o f t he s hell f rom t he co rner ( easily r ecognisable f rom t he m ould t hermocouple

measures) Application of tensile stresses to the solidification front in the off-corner region

The observations performed by CAS on different steels have put into evidence that the steels with high sulphur content show higher incidence of off-corner cracks than austenitic stainless steels. DUNAFERR collected and evaluated the results from former R+D projects to determine the effect of casting p arameters. T he most i mportant i nvestigation ca rried out b efore t he p resent p roject was a complex R&D work to prepare for casting output increase based on increased metallurgical length and with the use of a control system that would better utilise the geometrical amenities of casting machines.

20

Within t he f ramework o f t his work, i sotopic t racing i nspections were car ried out an d comprehensive mathematical modelling began.

The ap plied h eat transfer model proved c apability of m athematically d escribing t he s teady-state conditions in continuous c asting. T he de finition o f i nput da ta a nd m aterial pr operties ne cessary f or operation was granted extra attention. This model provides temperatures, liquid pool depth, solid shell thickness, etc. for the entire length of the continuously cast slab, on the basis of which the technology can be optimised according to the unique features of the casting machine.

Comparing th e r esults o f is otopic te sts c arried o ut a t d ifferent c onditions a nd th ose o f c omputer modelling clearly proved the reliability of modelling results.

FEM in vestigation of th e s teady-state casting p rocess ca rried out b efore t he present p roject cal led attention to significant difficulties that was found hard to interpret before. Of these difficulties, the most important ones were the following.

• It was proved that the shape of the liquid pool is not parabolic in cross-section, but rather, it e nds in tw o e xtensions (dog-bone). S olidification ceas es at ab out 2 40 m m f rom t he narrow s ides o f t he s lab. This i s one o f t he r easons for i nternal d efects i n t he f inished product.

• It w as r evealed th at is otopic tr acing d oes n ot s ignal to tal li quid p ool d epth, o nly th e border of t he mushy zone. This had to be t aken into account when t argeting a t higher casting speed

AALTO has determined the following features with casting parameters and product quality. They can be cal culated wi th t he m odels o r d etermined wh en k nowing t he s teel co mposition and p rocess parameters: • Microsegregation index describing the uneven distribution of chemical elements

- Microsegregation can l ead t o macrosegregation wh ich i s, o f c ourse, m ore h armful, an d dependent on melt flows because of bulging, solidification shrinkage, roller taper and wear and eccen tricy o f t he r ollers ( in s labs), m ini-ingots e tc. o ccurring dur ing c asting. T his microsegregation i ndex h owever gives the “ initial c onditions” f or t he macrosegregation severity of the steel composition being cast.

• Length of the mushy zone - The lo nger is th e m ushy z one d uring c asting, th e g reater is th e s ensitivity for internal

cracks. The length of the mushy zone is affected by steel composition by its liquidus and solidus t emperature d ifference, b ut al so t he p rocess p arameters, es pecially cas ting s peed lengthens the mushy zone.

• Vicinity of certain events (temperatures)

- As s teel s hrinks d uring s olidification, p ossibility f or c rack f ormation in creases if s olidus temperature and austenite formation temperature are close to each other (δ-ferrite the first phase in solidification) (as CAS also mentioned above). In this case, when the steel has just solidified and reached hardly no ductility (zero-ductility temperature when fraction of solid is = 0.99), steel shrinks because of the phase transformation from δ-ferrite to austenite. This additional s hrinkage m ight b e c ritical f or cr acking. T he s ame ef fect h appens i f austenite formation temperature is close to zero-strength temperature, which means that steel has just started to obtain its initial strength and right after that the phase transformation shrinks the steel structure and cracks might be formed.

• Corner temperature of the cast strand and harmful precipitations - As corners of the cast strand cool down faster due to the geometry than other parts of the

strand, co rner t emperatures h ave t o b e co ntrolled wel l es pecially during be nding a nd straightening t o a void c racks. Harmful p recipitations A lN an d Nb C ca n b e f ormed i f surface t emperature o f t he cas t s trand f luctuates o r co ols s lowly d own i n f ormation temperatures (700-900°C) of these compounds.

21

These above mentioned features can be calculated wi th IDS solidification model and Tempsimu heat transfer model of AALTO for defined steel grades of the industrial partners. In t he pr evious na tional pr oject AALTO has m ade a r esearch f or R uukki Raahe S teelworks f or optimising the Submerged Entry Nozzle (SEN) in continuous casting. The effect of different parameters on th e s teel f low in th e m ould, w ere i nvestigated. According t o th e f luid f low s imulations, c ritical parameters or features were determined. Critical parameters were surface velocity in the mould (Figure 1-1a), surface wave height (Figure 1-1b), turbulent kinetic energy, impinging velocity penetration depth of SEN. Safety ranges for these critical parameters were derived in order to obtain good as-cast quality (Table 1-4). In the following are results from the research.

Figure 1-1. Dependency of steel a) surface velocity and b) free surface wave height on casting speed. Mould:

1.75mX0.175m. Immersion depth: 140 mm. SEN type: sen1, sen1+5mm, sen1+10mm. Nozzle port: 85X(45,50,55). Nozzle angle: -10, -15, -20 degree. Casting speed: 1.40, 1.55, 1.70 m/min.

Table 1-4. Determined critical parameters and safety ranges for them.

Critical parameters Safety ranges Surface velocity [m/s] 0.2-0.3 Surface wave height [mm] 10-20 Turbulent kinetic energy [m2/s2] 0.025-0.04 Penetration depth [m] 2.0-4.0 Impinging velocity [m/s] 0-0.25

DUFERCO collected influencing factors for the main surface defects on castings (Table 1-5).

Table 1-5. Influencing factors to the main surface defects.

10

12

14

16

18

20

22

24

1.2 1.3 1.4 1.5 1.6 1.7

Casting speed, m/min

Sur

face

wav

e he

ight

, mm

SEN1,-15 degSEN1+5mm,-10degSEN1+5mm,-15degSEN1+5mm,-20degSEN+10mm,-10degSEN+10mm,-15degSEN+10mm,-20deg

0.2

0.25

0.3

0.35

1.2 1.3 1.4 1.5 1.6 1.7

Casting speed, m/min

Surf

ace

velo

city

, m/s

SEN1,-15 degSEN1+5mm,-10degSEN1+5mm,-15degSEN1+5mm,-20degSEN+10mm,-10degSEN+10mm,-15degSEN+10mm,-20deg

22

2.3.2 WP2 SIMULATION OF MOULD POWDER BEHAVIOUR The m ain o bjective of t his WP w as t o develop m odels t o s tudy t he m ould pow der phe nomena ba d casting q uality an d t o d etermine i mportant f eatures an d s afety ranges f or t he q uality co ntrol. DUNAFERR studies heat t ransfer phenomena of the s trand. The partners in this WP are CSM, BFI and DUNAFERR. The models will be applied for industrial validations and testing in WP5. Task 2.1 Thermal transient model of powder heating and melting (CSM) CSM has carried out the development of “Liquid pool model”, which is able to simulate the heating and melting of the mould lubricating powder on the meniscus. It is able to calculate the time evolution of liquid, sintered and powder layer thicknesses on the meniscus. This model is based on the work carried out b y Nakano et al . [12] and was formerly de veloped w ithin t he g eneral pur pose F EM c ode MSC.MARC. It was a 1D thermal model able to compute also the displacements related to the density variation of the material induced by the sintering reaction. In this respect, the model is non-linear, because the thermal field depends on the thicknesses of the three layers, which, in turn, depend on the temperature, through the density. In the model, the sintering reaction is described via a kinetic equation representing the time and t emperature ev olution of t he void fraction of t he material, wh ich t he t hermophysical p roperties depend from. The main input data for the “Liquid pool model” are listed in Table 2-1.

Table 2-1. Main input data for the “Liquid pool model”.

id consumption [kg/ton]

meniscus temperature [°C]

sinterisation temperature [°C]

size [mm]

casting speed

[m/min]

initial powder thickness [mm]

1 0.25 1525 1000

200*200 1.6 100 2 0.1 1525 1000 3 0.25 1553 1000 4 0.25 1525 900

“The Liquid pool model” has been upgraded by including the capability of simulating powder additions during c asting. T his t ask ha s be en a ccomplished b y w riting a us er s ubroutine w ithin t he FEM c ode MSC.MARC and b y modifying the s tructure of the MSC.MARC input f ile. As a result of the model

23

‘revamping’, the computational domain includes the initial powder layer and all the layers subsequently added (the number of additions in the simulation is defined in advance). At run start, (“initial state” in Figure 2-1), only the domain portion representing the initial powder layer is “act ive”. On t he t op, t he h eat t ransfer b etween p owder s urface an d am bient i s r epresented as boundary condition (“boundary A”). The thermal and phase evolutions of this layer are simulated until the first addition occurs, including powder consumption. At t he t ime o f po wder a ddition, t he domain po rtion c orresponding t o t he a dded powder l ayer i s activated and the boundary condition A is moved on the top of it. Accordingly, the user subroutine for the calculation of t he output variables ( thickness of t he l iquid, s intered and powder l ayers) has been modified in order to account for the powder additions. An e xample of o utput i s s hown i n Figure 2-2, c onsisting o f th e results in te rms o f each la yer le vel present on the meniscus: liquid slag, sintered material and powder at the base state. Further i mprovements i n t he CSM’s "Liquid pool m odel" ha ve c onsisted o f a c alibration s tage a nd testings with the available pool height measurements.

Figure 2-1. Sketch of the simulation of powder addition in CSM “Liquid pool model”.

Figure 2-2. First simulation with CSM enhanced “Liquid pool model”, including powder additions. The following actions have been made for improving the model:

24

Introduction o f a t emperature-dependent s interisation k inetic ( void r atio β as a f unction o f time)

( )( )300 1 ttTK −−⋅= ββ with ( ) TREs

eaTK ⋅−

⋅= (1)

where 0β is the initial void ratio, ( )TK is the sinterisation reaction rate with activation energy

SE (with a fitting parameter), 0t is the sinterisation start time.

Modification o f t he de nsity de pendence o n t he v oid r atio β , ch anging i t f rom a wei ghted average behaviour to a step behaviour, the latter being more representative of powder heating and m elting d ynamics. It can b e d escribed as f ollows: the c arbon f ilm e ntraps t he po wder molten particles until i t i s completely burned; the melt powder s tarts to behave as a co herent liquid only when sinterisation is almost complete ( β <0.01). The two different “density versus void ratio” behaviours are compared in Figure 2-3.

Figure 2-3. Comparison between average and step density behaviours versus void ratio. Task 2.2 Two-phase fluid-dynamics model of the steel/slag system (BFI)

Mathematical m odelling ap proaches we re d eveloped an d ap plied by BFI to g et in formation o n th e liquid flux thickness and velocity distribution at the interface between steel melt and liquid flux. The numerical model to investigate the interface between the two fluids was validated with the results from the experimental data received from the physical simulations from Task 2.4. Numerical model For the development and adaption of the numerical two-phase fluid-dynamic model the unsteady solver of a finite volume programme was used. The Reynold`s Averaged Navier Stokes equations were used to compute the fluid flow field inside the mould. To c ompute t urbulence i n t he f low f ield o f t he m ould a t urbulence m odel w as c hosen f or t he computation of the fluctuations of flow variables. Beside the s tandard k-ε turbulence model the more advanced realisable turbulence model, using the computation of the turbulent viscosity, was used

ε

ρµ µ²kCtur = . (2)

25

Here Cµ is no longer a constant, like in the standard k-ε turbulence model, but a function of mean strain and rotation rates, the angular velocity of the system rotation and the turbulence field (k and ε). For modelling of more t han o ne pha se i n t he c omputational do main ( liquid s teel a nd l iquid f lux) a multiphase f low model was ch osen. The volume of f luid (VOF) model was t he most s uitable model comparing c omplexity with c omputational a ffords a nd t ime. T his m odel s imulates t wo or m ore immiscible fluid phases (primary and secondary phases), in which the position of the interface between the fluids is of interest. In contrast to an Eulerian approach, where a set of the momentum equations for every fluid is used to solve the flow field, the VOF model uses a s ingle set of momentum equations. The volume fraction of each of the secondary phases tracked throughout the domain was computed by an equation for the qth phase of the form

( ) ( ) ∑=

−+=

∇+∂∂ 2

1

1p

qppqqqqqqq

mmSut qαραρα

ρ

. (3)

The source term is generally set to zero on the right hand side of Equation 3. The volume fraction of the primary phase was computed from

∑=

=n

qq

1

1α . (4)

Important material data like the contact angle and the interfacial tension between steel melt and liquid flux were also taken into consideration as well as the casting powder properties. Validation of the Two-phase fluid-dynamics model The numerical model was validated in a first step with results from the undertaken measurements at the physical model in task 2.4. Velocities in the centre plane of the mould model were measured with the Particle Image Vel ocimetry (PIV). The comparison o f t he velocity p rofiles measured i n t he p hysical simulation and computed in the numerical computations for a casting speed of 0.9 m/min, an immersion depth o f 120 mm a nd a n o il f ilm t hickness o f 60 m m a re s hown e xemplarily in Figure 2-4. M ould powder t hicknesses ( all l ayers) i n t he m ould r anges f rom 45 –60 m m a nd the r ange of t he oil thicknesses, s imulating t he l iquid f lux, w as c hosen t o 10, 30 a nd 6 0 mm t o c over t he wh ole range, including extreme values. The velocity profiles drawn from the centreline at the interface are in good agreement.

numerical computation physical simulation

x

z

y

26

Figure 2-4. The computed and measured velocity profile at the interface, in the centre line of the mould, for a casting speed of 0.9 m/min and an oil film thickness of 60 mm.

The validated numerical model is transferred to the s teel melt/liquid f lux f low by using the materials data for the selected steel grade and the mould powder collected and thermal boundary conditions from DUNAFERR. The liquid and the sintered fraction of the mould powder are identified by Tliquidus and Tsolidus of the mould powder in the computed temperature field inside the mould powder layer, Figure 2-5. When the mould powder becomes liquid a velocity field inside the liquid flux is induced by the steel melt flow. The model was calibrated in Task 5.4 and computations executed with the provided date in Task 5.6.

a) b)

Figure 2-5. Liquid fraction of the mould powder computed with the numerical model temperature field and liquid fraction b) velocity at the interface.

Task 2.3 Fluid dynamics model of the flux infiltration (CSM) With the aim of investigating the oscillation mark formation as related to the fluid-dynamics arising in the liquid f lux la yer in side th e mould-shell gap, t he i nitial p lan o f d eveloping a n ew model w ith th e FEM code FLUX has been changed into a more fitted and integrated solution. The ne w a pproach ha s c onsisted i n u pgrading a n e xisting, i n-house de veloped c ode, “ Liquid f lux infiltration model”, which p rovides a s olution for th e velocity and p ressure f ields inside the shell-to-mould gap, similarly to what planned. As an improvement to the original plan, the model estimates the shape o f t he m eniscus ( based o n B rimacombe’s D ynamic Meniscus Theory [14]) a nd simulates th e formation o f t he o scillation m arks as a consequence: t his i s v ery u seful t o g et u nderstanding o f t he origin of defects connected to the lubrication problems. The model provides an analytical solution based on the following assumptions: Slag is a Newtonian fluid Flow is one-dimensional in the casting direction (not true near the meniscus curvature)

27

Viscosity is temperature-dependent viscosity Gap thickness is constant along the casting direction Solid flux layer velocity is computed by a weighted mean of casting speed and mould velocity

The assumptions in the Dynamic Meniscus Theory are the following: Meniscus is free of a rigid (solid) skin Meniscus attains its equilibrium instantaneously

To cal culate the meniscus shape, φ, and the pressure and velocity f ields, the “Liquid f lux in filtration model” u ses t he i terative p rocedure s hown i n Figure 2-6. To make t he m odel ab le t o cal culate t he oscillation mark profile, a critical review of the hypotheses considered in the fluid-flow model of mould flux infiltration has been carried out and a few modifications have been introduced, one of them being the possibility of following the trajectory of meniscus point in contact with the mould.

Figure 2-6. Approach to modelling of fluid-dynamics inside the mould-shell gap and calculation of meniscus shape.

An example of the results provided by the model is shown in Figure 2-7. The black curves represent the shape o f t he m eniscus a t v arious i nstants d uring the o scillation c ycle, while th e b lue c urve is th e resulting oscillation mark profile; the end of each black line close to the mould wall is the contact point between the steel and the slag/mould. After the mould velocity reaches i ts maximum upwards, the position of the contact point changes for two reasons: Slab is moving downwards due to the casting speed Shape of the meniscus is changing, due to the liquid slag fluid-dynamics

The t rajectory of t he c ontact po int r esults f rom t he c omposition s uch t wo displacements an d i t represents the shape of the oscillation mark.

28

Figure 2-7. Results of CSM “Liquid flux infiltration model”. The oscillation mark profile is the trajectory of meniscus point in contact with the mould when the mould speed is its maximum upwards.

Task 2.4 Performance of supplementing physical model trials for provision of additional basic information as well as boundary conditions (BFI) Physical model t rials were executed in a full scale Perspex® model of t he mould in Figure 2-8. With regard to the similarity criteria the two-phase flow was simulated with water and oil simulating the steel melt and the liquid flux layer. A wide range of casting parameters were investigated such as: two SEN geometries ( Figure A -1), three d ifferent casting speeds (0.6, 0.9, 1.2 m/s), immersion depths of SEN (80, 120, 160 mm) and o il f ilm thicknesses (10, 30, 60 mm). The investigated casting speeds in the physical s imulations we re e xtended t o higher cas ting s peeds t hat wer e u sed i n t he v ertical cas ter o f DUNAFERR. This was undertaken to show that the model is capable to investigate the limits and see oil entrainment. Thus 54 experiments were undertaken in total.

Figure 2-8. Physical Perspex® model of the mould with PIV measurement system.

29

A num ber of different measurement t echniques wer e used i n the physical simulations to g ive information on the interface between the two phases and the fluid flow in the mould that were: • Flow visualisations to get information on the wave height at the interface of the two fluids and

possible entrainment of simulated flux. • PIV – measurements to g et d etailed in formation o n th e f low f ield in t he s imulated m elt a nd

liquid flux, especially to get information on the flow velocities at the interface. When setting up a physical model for fluid dynamic processes the similarity criteria were kept and the following r elevant d imensionless n umbers w ere ta ken in to a ccount. T he s imilarity of f luid f low was approximated w ith r espect t o R eynolds a nd Froude num ber. T he s imilarity of dr oplet e ntrainment i s captured w ith W eber num ber, w hich di ffers f or t he t wo f luid c ombinations of w ater/oil a nd s teel melt/liquid flux, Table A-3 (Appendix). The common praxis is to make allowance for a deviation from the Weber number, due to fact that there is no easy manageable analogous fluid combination that equals the p roperties o f s teel m elt/liquid f lux. The d eviation w as ta ken in to a ccount when in terpreting t he results, but similar physical simulations showed that the qualitative tendencies were transferrable to the steel melt flow. Flow Visualisations for the water/oil flow In the physical model flow visualisation of the water/oil flow showed the unsteady wave formation at the interface between water and oil film. The flow visualisations of the two-phase flow water/oil gave information on the wave heights at the interface and droplet entrainment form the oil with increasing casting speed. Exemplarily the visualised dynamic behaviour for three casting velocities and an oil film thickness of 30 mm were shown in Figure 2-9 for one point in time. Droplet entrapment was seen for the higher flow rates and wave heights, like in Figure 2-9c. In Figure 2-9d the wave heights for different casting speeds and immersion depth of the SEN are shown. The limiting range for the wave height of 15-20 mm is marked with a red colour gradient and should not be exceeded.

a) b)

c) d)

30

Figure 2-9. Flow visualisations of the interface for different casting speeds, oil film thickness 30 mm, a) VC = 0.6 m/min, b) VC = 0.9 m/min, c) VC = 1.2 m/min, d) wave heights for three immersion depth of the SEN

1.

From t he f low v isualisation t he wav e h eights at t he i nterface we re measured, Figure 2-10, a nd t he process p arameter´s, wh en en trainment of s imulated l iquid f lux t ook p lace we re evaluated. This was valid for higher casting speeds and lower immersion depth of the SEN where the wave height exceeded 20 mm. But this especially occurs when the velocities of the water flow exceed a critical value

( ) 4/1

248

−≥

oil

oilwatercritical

guρ

ρργ. (5)

With the material properties of water and the used oil a critical velocity of 0.23 m/s was computed from Equation 5, [13]. Dr oplet en trainment was o bserved i n t he f low v isualisations wh en t he v elocity measurements verified that the critical velocity was reached or exceeded (see PIV measurements Figure 2-11). All measured wave heights at the interface for the two SEN geometries are shown in Figure 2-10. The measured wave heights at the interface were h igher for the SEN 1 , this i s due to the port e xit angle. Critical wave heights are red. When the port exit angel i s d irected awa y f rom t he interface the wave heights can be diminished.

a) b)

Figure 2-10. Measured wave heights at the interface water/oil in the centre plane for different casting speeds, oil film thicknesses and immersion depths of a) SEN 1and b) SEN 2.

PIV Measurements in the physical model In t he m ould m odel, P IV measurements wer e m ade f or t he s ame r ange o f cas ting p arameters i n t he centre plane of the mould. The PIV measurements showed the velocities on the right half of the mould. The general flow field type for the two ports SEN is of the type “double-roll”.

31

PIV measurements were made with and without top covering oil film in the centre plane of the mould. An example for the PIV measurements in the mould is given in Figure 2-11 an immersion depth of the SEN 1 o f 120 mm an d t hree d ifferent c asting s peeds wi thout o il. I t can b e s een t hat f or t he hi ghest investigated casting speed of 1.2 m/min the critical velocity of 0.23 m/s computed from Equation 5 is reached at the surface in Figure 2-11c, (see also droplet entrainment in Figure 2-9c). With th e P IV measurements t he v elocities at t he s urface wer e d etermined f or d ifferent cas ting parameters and SEN geometries. In correlation with the flow visualisations a higher probability of oil entrainment was s tated f or v elocities g reater t han 0 .23 m /s, wh ich was i n g ood acco rdance t o t he theoretical velocity for possible oil entrainment of the used paraffin oil.

a) b)

c)

Figure 2-11. Measured velocities in the centre plane of the mould (one side) for SEN 1 (α = 0°), immersion depths 120 mm, and for a casting speeds of

a) vC = 0.6 m/min, b) vC = 0.9 m/min, c) vC = 1.2 m/min. The velocity profiles from the centre line at the surface were extracted from the measured flow fields. The individual velocity maxima of the simulated melt at the water/air surface in dependence from the casting s peed were s hown i n Figure 2-12. With th e increase o f t he cas ting s peed an d t he i mmersion depth the velocities at the surface increased. The velocities are smaller for the SEN 2 because the port exit angel is redirected from the surface.

32

Figure 2-12. Measured velocity maxima at the surface for different immersion depth in dependence from the casting speed for SEN 1 and SEN 2.

PIV measurements in the two-phase flow of water and oil A very n ew method was es tablished w hen t he v elocities wer e m easured i n t he wat er an d o il f low simultaneously. The flow field showed a vortex in the water flow induced by the fluid flow through the ports and a counter rotating vortex in the oil film, Figure 2-13. The velocities in the oil film were much smaller than in the flow field according to the different viscosities of the fluids and the friction on the interface.

a) b)

Figure 2-13. PIV measurements of the two-phase flow water/oil in the centre plane of the mould and SEN 2

for a casting speed of 0.9 m/min and an immersion depth of 120 mm.

33

Task 2.5 Adaptation of DUNAFERR model for the qualification of the liquid pool depth and the shape (DUNAFERR) For characterising the temperature field of the slab at DUNAFERR and at OBUDA evaluation system was developed. The surface temperature is changing along the cast slab because the cooling consists of rolls, water from nozzles and air cooling and this results in a complex temperature field. As an example, Figure 2-14 displays the surface temperature distribution both for the narrow and wide sides in a s lab part of one meter (for notations see Figure 2-15). For a relatively simple characterisation of the whole slab t emperature d istribution, p arameters r epresenting t he t hermal h istory of s urface p oints we re chosen. When the temperature history of one point on the slab is followed from meniscus to the end of the caster, the well-known cooling curve is obtained (Figure 2-16). The cooling curve analysis (Figure 2-17) calculates the following characteristics features:

• Number of intensive cooling cycles, i.e. the number of abrupt coolings from the meniscus to the end of the machine

• Summarised value of temperature drops occurred in the individual cooling cycles • Average value of temperature drops occurred in the individual cooling cycles • Maximum value of temperature drops occurred in the individual cooling cycles • Average value of cooling rates developed in the individual cooling cycles • Maximum value of cooling rates developed in the individual cooling cycles • Average value of reheating rates developed in the individual cooling cycles • Maximum value of reheating rates developed in the individual cooling cycles • Cross-sectional s urface temperature distributions in t he X 1 a nd Y 1 directions a t t he

characteristic levels of cooling system Steel co mposition, s uperheat an d co oling af fect t he t hermal h istory p arameters, t hus s urface co oling conditions and surface cooling homogeneity can be determined by this relatively simple way.

Figure 2-14. Surface temperature distribution in an industrial case.

Figure 2-15. Sketch of the slab with the modelling volume and important directions.

X1

Y1

Z1 Z3Z2

X2

Y2

Cas

ting

dire

ctio

n

34

Figure 2-16. Cooling curve of an individual surface point.

Figure 2-17. Analysis of the cooling curve.

Liquid pool depth and shape in the X2Z2 plane The depth and the shape of the liquid pool can be of primary importance from the point of view of the quality of cast semis and of the workability of the casting technology. A basic requirement is that the liquid pool depth calculated for t he solidus t emperature, a s a rule, must be shorter t han the e fficient length of the casting machine. In other words, when the level of the last supporting roll is reached, the cross-section of the strand must be solid. As an example, in Figure 2-18 showing the X2Z2 plane of the strand, the liquid pool depth (calculated for the solidus temperature) seems to be eligible because the solidification has f inished just before the l ast supporting roll. The W shaped (dog bone) sump i s t he result of intensive cooling of the centre region of the wide side. In the same figure the position of the liquidus l ine i s a lso pl otted be cause t he di stance be tween the l iquidus a nd s olidus c an be i mportant information, especially from the point of view of macrosegregation susceptibility. The line representing the position of the liquidus-1 isotherm gives information on the extension of the area with a temperature very close to the liquidus. Liquid pool shape in the X1Y1 plane at the exit of the mould and at the last supporting roll The cross-sectional (at right angles to the casting direction) shape of the liquid sump is controlled just at the mould exit and at the level of the last supporting roll. In Figure 2-19 both cross-sections can be seen together. These data help checking the solid shell thickness and its distribution along the perimeter of the m ould a t th e exit s ide. T his d istribution c haracterises th e s moothness o f t he s olid s hell a nd th e insecure p arts can b e r ecognised. T he expected l iquid s ump s hape at t he l ast supporting r oll gi ves information on the last part of the solidification and on the position of the last liquid inside the strand. .

0 2 4 6 8 10 12 14500600700800900

1000110012001300140015001600

Tem

pera

ture

, Cen

tigra

de

Distance from the meniscus level, m

"Local_Max" "Local_Min"

3,0 3,2 3,4 3,6 3,8 4,0800

850

900

950

1000

1050

1100

Reheating rate, K/s

CoolingrateK/s

Temperature drop

Cooling cycle

Tem

pera

ture

, Cen

tigra

de

Distance from the meniscus level, m

"Local_Max" "Local_Min"

35

Figure 2-18. Liquid pool depth and shape in the X2Z2 plane.

Figure 2-19. Liquid pool depth and shape in the Y2Z3 planes.

2.3.3 WP3 SIMULATION OF FLUID FLOW AND SOLIDIFICATION BEHAVIOUR The m ain objective o f th is WP is t o develop m odels to s tudy th e f luid f low, th ermomechanical behaviour o f m ould an d steel m elt, as wel l as s olidification p henomena an d t o d etermine im portant features and safety ranges for the quality control. The partners in this WP are CSM, BFI, DUNAFERR and AALTO. The models developed will be applied for calculation of industrial trials in WP 5. Task 3.1 Development of a steady-state 3D thermo-mechanical model of the mould (CSM) A so-called “inverse approach” has been used to get the temperature map at liquid-solid steel interface (see Figure 3-1). A 2D steady state finite difference model (Task 3.2) of the longitudinal section of the mould is applied for each vertical line of thermocouples. The model actually takes as input the heat flux curve an d i s made run until the convergence on t he t emperature values i s r eached. S tarting f rom t he thermocouple data (average heat flux and casting speed), heat flux distribution and temperature at the interface are calculated. The i n-mould he at f lux c urves r esulting f rom t he FDM a nalysis a pplied t o t he mid-face an d co rner regions h ave b een u sed t o d erive t he h eat f lux cu rves al ong t he cr oss-section perimeter at d ifferent distances f rom t he m eniscus. Because of t he s ymmetry with r espect t o t he mid-face, a q uadratic function has been used. This result has been used as input for both the 3D mould model (in this task) and for the 2D solidification model (in Task 3.2).

0 1 2 3 4 5 6 7 8 9 10 11 120

100

200

300

400

500

600

700

800

Supporting rolls

Driven rolls

Liquidus, liquidus-1 and the solidus temperaturesSuperheating=30 K, vcast=vnom

Half

widt

h of

the

slab,

mm

Distance from the meniscus level (Z), m

Liq Liq1 Sol

0 20 40 60 80 1001200

100

200

300

400

500

600

700

800

Superheating=30 K, vcast=vnom

Liquidus,liquidus-1 and solidus temperaturesbelow the mould and at the last supporting roll

Below the mould, liquidus Below the mould, liquidus-1 Below the mould, solidus Last supporting roll, liquidus Last supporting roll, liquidus-1 Last supporting roll, solidusW

ide

side

(X),

mm

Narrow side (Y), mm

36

Physical scheme

InputCasting speed

Average heat flux

Thermocouples measures

OutputHeat flux distribution

Calculated temperature

Mould Glass

Steel Liquid

Thermocouples

Physical scheme

InputCasting speed

Average heat flux

Thermocouples measures

OutputHeat flux distribution

Calculated temperature

Mould Glass

Steel Liquid

Thermocouples

Figure 3-1. Inverse model for the derivation of heat flux.

The steady-state 3 D t hermo-mechanical model h as b een d eveloped, b ased o n t he f ollowing m ain assumptions: Double symmetry and steady-state condition Perfectly straight mould same heat transfer conditions for each side Copper assumed t o b e an el astic-perfectly p lastic material wi th t emperature dependent

properties The following thermal boundary conditions are imposed: Heat flux map at mould contact with steel Heat t ransfer coefficient and water temperature in the zone of forced convection with cooling

water Temperature dependent heat transfer coefficient in zone of radiation heat exchange mechanism

prevailing Both heat transfer coefficient and air temperature in the zone of free-convection-with-air

Finally, the following mechanical boundary conditions are imposed: Symmetry constraints Contact between mould and ring Ferrostatic pressure

A t hermo-mechanical an alysis h as b een p erformed t o as sess t he s tress-strain f ields i nduced by t he thermal loading a nd by th e a pplied c onstraints. T he m ould g eometry s ubmitted to th e f inite e lement method ( FEM) solver (MSC Marc 2005r3) has not t aken into account t he t aper contribution and has been m eshed i n a bout 121 000 8 -node br ick elements (Figure 3-2) The m echanical and thermal boundary conditions have been defined as well as the initial conditions. The mesh has been built using the pre-processor MSC.MENTAT and the dedicated software HyperMESH. The temperature field resulting from the 3D thermo-mechanical FEM simulations of the mould must be compared to the experimental data at corner and mid-face regions. I f a s atisfying agreement i s found with the heats of the steels considered, the computed temperature stationary field reached by the mould when submitted to the heat flux can be employed as input for computing the mechanical evolution of the mould itself.

37

Figure 3-2. Geometry and mesh of the mould FEM model. Task 3.2 Development of a transient 2D thermo-mechanical model of the solidification in the mould (CSM) In the transient 2D thermo-mechanical model solidification is described by the “travelling slice model” (Figure 10) . The f ixed grid in space represents one quarter of b illet section. The computational g rids (mesh) for the FEM models have been set-up taking into account the double symmetry of the domains and that the inner part of the billet cross-section is not involved in the in-mould solidification.

Heat transfer and stress analysis are coupled, and time-dependent heat flux profile simulates travelling of the steel inside the mould. Moreover, elasto-plastic constitutive Equation 6 is used as follows:

)()(

)()()(2

TT

TTET el

h

el

εεεσ ⋅

⋅=

(6)

where )(Tσ is the total equivalent stress )(Tε is the sum of elastic and plastic equivalent strain components )(TE is the Young modulus vs temperature curve (source literature data)

)(Telε is the elastic strain vs temperature curve (source literature data);

2h is the hardening parameter (source literature data). A t hermo-mechanical an alysis h as b een p erformed t o as sess t he stress-strain f ields during th e solidification without the contribution of ferrostatic pressure. The steel geometry submitted to the FEM solver MSC M arc 2005r 3 ha s be en m eshed i n a bout 5 200 8 -node g eneralised p lane s train el ements (Figure 3-3). The s hell s urface g eometry i s o btained f rom t he co mputed d isplacement i n t he cr oss-section p lane as a f unction o f t ime. ( Figure 3-4). The di splacement f ields of bo th the mould and the steel allow computation of the gap between them. (Figure 3-5).

38

gap (z)

distorted mould (z)

shell surface (z)

gap (z)

distorted mould (z)

shell surface (z)

perimeter at the meniscus

displacement (z)

perimeter at the meniscus

displacement (z)

Solid shell

Heat flux

Meniscus level

Time →distancebelow meniscus

Time

Displacement

Figure 3-3. 2D steel FEM model, 5200 8-node generalized plane strain elements.

Figure 3-4. 3D representation of the 2D steel model evolution.

Figure 3-5. Displacement map on the outer shell surface, the highest shrinkage is around the corner.

39

Task 3.3 Development of a steady-state 3D thermo-fluid-dynamics model of the strand (BFI) BFI developed a numerical model capable of computing the velocity and temperature distribution along the complete strand to obtain more detailed information on the temperature field and the shell thickness. The co mplete l ength o f t he v ertical p art o f t he co ntinuous cas ter at DUNAFERR has a l ength of approximately 1 0 m ( see T able A-1). T he wav e h eights at t he steel m elt/liquid f lux i nterface wi th approximately 0.02 m are very small compared to caster length. Therefore the influence of the interface waves o n t he velocity an d t emperature d istribution al ong t he co mplete s trand was n eglected an d a numerical model was developed computing the single phase of the steel melt. For the here mentioned numerical model the top surface was a wall with a heat transfer similar to the heat transfer through the mould powder. An additional reason why a single phase model was used for the complete strand was that the size of the numerical grid will be huge and lead to a high number of grid cells due to the length of the strand. This made a r eduction in the used numerical models necessary to reduce computation t ime. The numerical model w as able t o c ompute t he f low f ield, t he t hree di mensional s hell of t he s trand a nd t he metallurgical length in dependence of the cooling conditions at the different cooling zones. For the numerical computation of the solidification process, a phase change model (liquid to solid and vice versa) was applied. This considers the withdrawal of the solidified strand shell, the latent heat of the solidifying/melting fluid, and the influence of the mushy zone on the flow field. The mushy zone exists in the regions where the fluid temperatures lie within the solidus and liquidus temperature. In this region a sink for momentum applies in the following form:

( )( ) ( )ici uuA ,3

1−

+−

εββ . (5)

Where β represents t he l iquid f raction ( 0 equals solid and 1 e quals l iquid) ε was a s mall n umber t o prevent division by zero. A n umerical g rid f or th e c omplete s trand w as s et u p. T o m inimize g rid in fluence o n th e n umerical results a s tructured g rid was i mplemented f or t he c omplete s trand co ntaining o nly h exahedral cel ls. Special t reatment o f t he b oundary z ones wi th a b oundary l ayer g rid f or a b etter cap turing o f t he solidification i n t he m ould a nd s trand w as unde rtaken. T he g rid of t he complete s trand h ad approximately 1.5 mio. c ells. Ov erall a t hree d imensional t hermo-fluid-dynamics m odel, ta king solidification o f th e s teel m elt in to a ccount, w as e stablished to m odel th e v elocity a nd te mperature distribution along the complete strand.

In Figure 3-6 the temperature and velocity distribution for a set of defined process parameters is shown. On t he l eft s ide t he temperature d istribution at t he s trand s urface can be s een. T he t emperature distribution showed the typical cold temperatures at the corners of the slab and a reheating after the end of the secondary cooling zone. The velocity distribution is shown from the centre face of the s trand. Inside t he m ould t he t wo p ort j ets wi th h igh v elocities can be s een. A long t he s trand the v elocities become small and uniform. The developed model was used in WP5 for the numerical computation for different process parameters.

40

Figure 3-6. Temperature and velocity distribution along the complete strand with regions of interest zoomed out.

Task 3.4 Adaptation and further development of the macrosegregation model (DUNAFERR) The objective in this task is the adaptation and further development of the macrosegregation model to the c ontinuous c asting process. A s tatistical a nalysis o f in dustrial d ata was car ried o ut i n o rder t o enhance t he r eliability o f t he m odel. An i ndustrial s cale d ata s et of t he casting of 4 00 s labs w ere analysed. It was expected that th e a nalysis c ould h elp to r eveal th e in terrelation b etween in dustrial parameters an d cen treline s egregation o r, as a m inimum, i dentify t he m ajor i tems t hat can have an influence on the inner quality of the slabs. The data set was from a curved casting machine and the as-cast samples were cut from steady-state cast s trands. The data set contained al l parameters which are important in determining segregation and which can be measured in industrial applications. The data set was completed with the mathematical modelling results of the steady-state casting of each of the 400 slabs, including IDS – solidification model (thermophysical parameters), TEMPSIMU – heat transfer model and BOS – bulging model (the models developed by AALTO). The dataset, which was used f or a s tatistical an alysis, was t hen acco mplished wi th t he r esults o f m athematical modelling of steady-state casting.

41

Introduction of LMI (Liquid Motion Intensity) model The m ain co nclusion o f s tatistical an alysis i s t hat t he ch anges i n t he v alue o f cen treline s egregation cannot be explained by the primary measurements during casting or by the direct data obtained from the heat t ransfer modelling o f continuously cas t s trand i n t he steady-state c asting conditions. Neither th e technological data do contain those data types which can directly be l inked to the value of centreline segregation. It seems ev ident t hat we h ave to t ake into ac count t he fluid f low acc ompanying solidification, r esulting i n m acrosegregation, an d t he parameters wh ich d escribe t he l iquid s upply compensating for solidification shrinkage. The problem is that in the mushy zone it is very difficult to monitor the fluid flow, the segregation and the change in the form of the solid shell in a real industrial case. At the moment there is no feasible complex mathematical model available. The co re i dea of t he LMI M odel o f OBUDA (subcontractor t o DUNAFERR) is th at th e f luid f low inside the strand is assessed from the shrinkage of the solid shell and from the constrained deformation which occurs because of the ferrostatic pressure and the supporting rolls and bulging etc. Based on the intensity of the f luid f low and the aggregation of the c yclic fluid f lows the parameters which can be taken into account as characteristic features of casting were generated. The LMI parameters describing the intensity of fluid flow can be calculated for real casting conditions [15,16]. Parameter LMI_7 can be interpreted as a particular quantity of liquid, until zero liquid quantity has been reached, so, until complete solidification. This parameter also indicates the value of the volume of pores forming in the slab centreline. After a certain level of solid phase has been reached, no more fluid flow is possible. It has been assumed – according to statistical analysis results – that flows inside the mushy stop when there are 20-30% of mushy liquid phase present. The pr oportion of liquid w hich i s s till able t o m ove de pends o n the dendritic s tructure, too, (columnar/equiaxed) an d s econdary de ndritic a rm s pacing. If t here i s no m ore l iquid s upply, t hen shrinkage pores will form. After parameter LMI_7 was introduced and included in the statistical analysis, the correlation between the es timated an d t he m easured cen treline s egregation was d ramatically i ncreased. T his s equence o f calculation was performed by the use of the LMI model, which is a rather time-consuming process, for 3 s teel g roups an d f or 3 8 cas es. During t he p reliminary cal culations i t b ecame e vident t hat t he correlation coefficient between the centreline segregation estimated by the model and measurements is influenced much by the chosen range of the parameter LMI_7. Application of LMI (Liquid Motion Intensity) model On the basis of LMI model for a given steady state casting process the following critical parameters can be estimated for the last period of solidification:

• Porosity in the centre part of the slab • Mushy liquid relative flow rate

Calculation m ethods o f t hese p arameters wer e d eveloped f or r eal cas ting conditions, ie . ta king in to account the shrinkage of solid shell, the positions of supporting rolls, the eccentricity of them and the bulging of the shell. The following figure shows the explanation of the porosity and the mushy liquid flow functions. Let us suppose constant roll gaps almost for the whole casting machine, it is represented by the blue line in Figure 3-7. The mushy zone starts in the centreline of the slab at about 5.5 m from the meniscus and the final solidification occurs at about 11 m . Somewhere in the middle of the mushy the f ree flow of mushy liq uid w ill stop (or drastically d ecrease) acc ording t he LMI model. More or l ess f ree f low of mushy liquid can be supposed in the first half of the mushy area, where the red line (representing the relative f low rate in mm/mm) in the figure is not z ero. The positive value of th is function means an upward direction of mushy liquid flow (flow to the direction of meniscus), the negative value represents

42

sucking process in the mushy area. At about 30% of mushy liquid the flow rate becomes zero according to the results of previous calculation. In the second part of mushy area the characteristic process will be the porosity formation instead of flow of liquid. The porosity can be characterised in the 2D model by area, so the unit of it is mm2. The black line represents the porosity developed in the final solidification stage.

Figure 3-7. Sketch for the explanation of porosity and flow calculations.

Figures 3-8 and 3-9 illustrate the practical use of the parameters in designing of casting technology. As an example the effect of di fferent tapers of supporting rolls on the expected porosity and l iquid f low rate is presented. A constant (but not zero) taper of supporting rolls was supposed.

Figure 3-8. Flow rate distribution of mushy liquid for different tapers.

0 2000 4000 6000 8000 10000 12000 14000-15

-10

-5

0

5

10

15

20

25

30

T=szoliduszT=liquidus

T<solidusliquidus>T>solidusT>liquidus

Temperature in the centerline of slab:

Flow rate in thebeginning of mushy

Porosity developedduring solidification

Finalporosity

Actualflow rate of

mushy liquid

Actual roll gap

End of flow of the liquid30 % mushy liquid

End of mushy 0 % mushy liquid

(end of solidification)

Beginning of central mushy zone60 % mushy-liquid content

Poro

sity,

flow

rate

Distance from meniscus level, mm

porosity 5000 x flow rate

110

111

112

113

114

115

116

117

118

119

120Taper from 4 m, mm/m

Half

of ro

ll gap

, mm

C

0 2000 4000 6000 8000 10000 12000 14000

-0.0015

-0.0010

-0.0005

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

Taper from 4 m, mm/m

Flow

rate

, mm

/mm

Distance from meniscus level, mm

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

43

Figure 3-9. Porosity distribution of mushy liquid for different tapers. Task 3.5 Adaptation and further development of the columnar to equiaxed transition model (DUNAFERR) In this task DUNAFERR is further developing a model for columnar to equiaxed transition (CET). Thermal field calculation for estimating the CET position DUNAFERR have calculated temperature field with 3D heat transfer model Tempsimu (by AALTO) and ev aluated t he act ual t emperature g radient an d co oling r ate valid i n t he m ushy z one f rom t he obtained results. The cooling rate can be determined for a given temperature, or for a given temperature range. Industrial experiments for CET determination Casting experiments were performed at DUNAFERR in order to clarify the situation around the CET (columnar to equiaxed transition)) under industrial conditions. Different heats and slabs were cast under controlled circumstances close to the steady-state casting conditions. Thermal parameter calculations and results in the CET region of slabs During c olumnar s olidification it c an be s upposed th at th e d irections o f th ermal gradient a nd o f dendritic growth are the same. In the last stage of solidification, when thermal gradient is very low, the released latent heat could cause reversed thermal gradient, but p revious calculations d id not p rove i t. The columnar dendrites grow continuously, and columnar to equiaxed transition will happen if in front of the dendrite tip the liquid is sufficiently undercooled, for a sufficient period of time. Naturally, the equiaxed growth is promoted if some solid particles, which enhance the heterogeneous nucleation, are present in the melt. It follows from the above mentioned s tatements that the thermal parameters close to dendrite tip will mainly induce the CET. Preliminary calculations showed that the expected growth rates of the dendrites close to the CET are around 0.1 mm/s and about a 1˚C undercooling of the tips can be supposed. These data are valid for al l of the investigated s teel compositions. According to these assumptions, thermal

0 2000 4000 6000 8000 10000 12000 14000-1

0

1

2

3

4

5

6

7

8 Taper from 4 m, mm/m

Poro

sity,

mm

2

Distance from meniscus level, mm

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

44

parameter cal culations wer e p erformed TLIQ-1°C (= t he t emperature o f a ctual l iquidus m inus o ne Centigrade wh ich i s more s table than T LIQ). The thermal g radient and cooling r ate d istributions were derived from the thermal field of the slab as a function of the distance from the wide side surface. The actual values of the thermal gradient and cooling rate functions were then determined just in the CET position which were previously measured by isotopic and conventional metallographic technique on the sections of the slabs. Evaluation of CET calculation results The m athematical an alysis o f d ata g ives t he p ossibility t o c reate a general p henomenological description of CET. By multiple l inear regression the individual e ffect o f carbon and sulphur can be taken into account, and a third parameter was also introduced in order to describe the cross-effects. The final result can be given in the following form: GLiquidus-1 = 0.166 – 0.398*[C wt%] + 5.870*[S wt%] – 17.797*([C wt%]*[S wt%]) (7) where GLiquidus-1 is the thermal gradient at the TLIQ-1°C, [C wt%] and [S wt%] are the carbon and sulphur content, r espectively. C orrelation an alysis was p erformed b etween t hermal g radients cal culated f rom the thermal field of the slabs and calculated by Equation 7. The correlation factor is 0.8, which is fairly good, taken into account the complexity of the columnar to equiaxed transition. Figure 3-10 represents a nomogram for different carbon and sulphur contents in the chemical composition range of experimental heats.

Figure 3-10. Nomogram for the thermal gradient threshold determination.

In the previous project, experimental results both from DUNAFERR and Ruukki (Finland) have proved the validity of this model. The use of this model presumes the precise knowledge of thermal field of the slab d uring s olidification in w hich th e e ffects o f c asting p arameters ( i.e. s uperheat, c ooling in tensity distribution, p hysical p arameters o f the cas t s teel, etc.) a re taken i nto acc ount p roperly. As a consequence the thermal gradient at CET position can be regarded as the main factor, which determines the change of the solidification pattern. This thermal gradient threshold depends only on the chemical composition o f t he s teel. T he r elatively g ood co rrelation b etween t he m easurements an d cal culated values prove the governing role of the thermal gradient, but other elements with less partition ratio and other circumstances (fluid flow, bulging, etc.) can also affect the thermal gradient threshold.

0.004 0.006 0.008 0.010 0.012 0.014 0.0160.12

0.14

0.16

0.18

0.20

0.22

0.24

0.26

0.28

0.30 0,05 wt% C 0,08 wt% C 0,1 wt% C 0,13 wt% C 0,15 wt% C 0,18 wt% C

Ther

mal

gra

dien

t at C

ET, K

/mm

Sulphur content, wt%

45

Task 3.6 Solidification model (AALTO) The o bjective of AALTO in t his t ask was t o f urther de velop a nd a pply C DG m odel ( Constrained Dendritic G rowth) wh ich i s a t hermodynamic-kinetic m odel f or cal culation o f C ET ( columnar t o equiaxed transformation) in the cast strand. Further developing the model was finished because several rather much af fecting p arameters would h ave r equired t oo l ong i nvestigation i n o rder t o get s ensible results. In addition it w as seen more appropriate for th is p roject t o further develop IDS solidification model. The r esults g iven b y IDS m odel af fect solidification an d h eat t ransfer cal culation r esults wh ere IDS calculates liquidus and solidus temperatures, thermophysical material data as a function of temperature (enthalpy, thermal conductivity, density). As well as so-called “Quality Indices” which were determined (WP5 Task 5.6) are calculated from the databases of IDS and austenite decomposition model ADC (WP 4 Task 4.1) IDS solidification model IDS is solidification and microstructure model for low-alloyed and stainless steels [17-20]. The model is b ased o n th ermodynamic a nd k inetic th eories o f s olidification. It a lso u tilises la rge a ssessed thermodynamic databank, as well as, regression formulas of experimental data. IDS includes two main modules, the solidification module and the austenite decomposition module ADC. Both modules have their own recommended composition ranges. IDS calculations take into account the effect of solutes C, Si, Mn, P, S, Cr, Mo, Ni, Cu, Al, N, Nb, Ti, V, Ca, B, O and H, cooling rate and dendrite arm diameter. Also formation of inclusions and precipitations are included in the model as shown later in calculations of steel compositions of DUFERCO and CAS in WP5. Steel composition and cooling rates is given for the model an d i t cal culates phase t ransformation t emperatures, p hase f ractions, microsegregation a nd thermophysical and other material property data (Figure 3-11).

Figure 3-11. Input and output data of IDS model.

In DEFFREE project AALTO has de veloped a nd i mproved IDS s olidification m odel b y making a broad literature search and utilising the experimental data found. The extension and/or improvement of Gibbs’ energy databanks has been performed by assessing a large amount of ternary phase system data of s teels. Also, a major material p roperty d ata s et h ave b een co llected an d as sessed. A mong others, accurate material property data, such as enthalpy, thermal conductivity and density are essential for heat transfer calculations of continuous casting (Tempsimu and CastManager process simulation). All this research has made it possible to widen the composition ranges of steels in IDS calculations in order t o enable solidification s imulation of new s teel g rades and to ach ieve more accu rate r esults. In Figure 49 i s an example of showing the importance of the work made in this area, when in this case more s olidification d ata o f b oron s teels h as b een gathered an d assessed. On t he l eft i s a b asic Fe-C-binary diagram, which is compared with a Fe-C diagram with a boron addition from 0.001% to 0.003% (on the right). Figure 3-12 shows the dramatic effect of boron addition decreasing the austenite phase.

Input

Output

Phase change temperatures Phase fractions Microsegregations Inclusions and precipitations Enthalpy Specific heat Thermal conductivity Density Thermal contraction Liquid viscosity Liquid/air surface tension Solid/liquid interface energy

Steel composition Cooling rate Dendrite arm spacing (also default values)

46

Figure 3-12. On the left: Fe-C phase diagram, on the right: Fe-C phase diagram with boron addition from 0.001% to 0.003%.

In Figure 3 -13 o xide in clusion s ystems ( X-O an d Fe-X-O) h ave b een as sessed, wh ich i s an other example of the development work of IDS. This has enabled the model to simulate the formation of new inclusions.

Figure 3-13 a) Calculated oxygen solubility in liquid Fe-Al alloys at 1600°C, together with experimental data points.b) Calculated isothermal section of the Fe-Ti-O system at 1300°C.

47

Task 3.7 Adaptation of the DUNAFERR model for the prediction of the temperature evolution in the strand and prediction of surface and inner cracks formation (DUNAFERR) Creep laws applicable in practice During s olidification o f s lab, th e connection b etween th e s trains and s tresses d eveloping in th e s olid shell is established by the relationship which is valid, on one hand, for elastic strain and, on the other hand, for p lastic s train. In t his r esearch work M izukami’s equation [21] was used for cal culating t he elastic modulus and Kozlowski’s models [22] (1A, 2, 3) were applied for creep analyses. Approach of creeping under continuous casting conditions The s lab s urface i s af fected b y cyclic t hermal ef fects, wh ich ar e t he r esult, i n t he f irst p lace, o f t he cooling effects on its surface and also of the subsequent reheating. During the cooling of the surface the thermal s hrinkage o f t he s urface i s h indered b y t hat p art o f t he m aterial wh ich is u nder t he s urface, closer to the middle of the slab and this leads to tensile stress on the surface. Because of this stress creep processes d epending o n t he act ual t emperature d istribution s tarts an d t his, o f co urse, d ecreases t he actual stress level. During reheating the same phenomenon exists but the other way round: the thermal expansion of the surface is hindered by the subsurface area and this leads to compressive stress and, in its t urn, again generates a c reep s train. In t his ap proach we p resume t hat s tresses in th e d irection o f thickness are insignificant as compared to lateral stresses. Surface crack development criteria Schwerdtfeger offers a practical approach, calculating the condition system of crack development from the value of reduction of area measured during the tensile test [23]. There are a lot of presumptions in his article too but still, at the end he offers, for a very limited range of composition though, a practically feasible calculation of the criteria of surface crack development condition. Introducing the term ’accumulated damage’ The reduction of a rea measured during a t ensile test at a g iven temperature defines a s train which, at this temperature, can be called a critical strain because after this strain value has been reached, rupture will ha ppen. A t a g iven c omposition a nd a t g iven te st c onditions ( strain r ate, th ermal h istory), th e critical strain depends on the temperature. According to the basic idea of Schwerdtfeger [23], even if a strain does not reach the critical value a t a g iven temperature, the damage incurred as a r esult of this strain w ill s till r emain or w ill a ccumulate in th e s tructure. If a s train (whose value is le ss th an th e critical value) develops at a given temperature and next we move on to another isotherm where a strain (whose value is less than the critical value) also develops, then the damage effects of s trains at these two different temperatures will accumulate. Application of the model In the case of steels with a content of 0.15% C, 0.3% Si and 1.4% Mn the development of accumulated damage was analysed. In order to define the crack formation criteria, the following let us presumptions were made:

• [%Al][%N] = 0.0002 • Strain rate = 0.0001 1/s (in this approach an average strain rate is applied) • Cooling rate = 1 K/s (in this approach an average cooling rate is applied) • Value of f parameter = 6.66

Accumulated damage functions calculated by Kozlowski’s creep models 1A, 2 and 3 [22] are shown in the d iagram. In each of t he t hree cr eep f unctions, t he v alue o f t he accu mulating d amage p arameter exceeds 1. The value of f parameter must be defined for the particular casting machine. On the curved

48

casters it i s eas y t o d iscern wh ich p arts o f t he cas ting m achine cau ses the b iggest i ncrease o f t he accumulated damage. In this case the biggest intensity can be observed between 4 and 6 meters (Figure 3-14).

Figure 3-14. Accumulated damage functions calculated for a real casting case. Conclusions Experiences shows that this ‘accumulated damage’ model can be used to characterise the development of slab surface cracks and to map the effects of technological changes on crack formation. The analysis can be made along a l ine (along the casting direction) and on the surface as well, both under steady-state and transient casting conditions. Further development of the model is necessary because there are uncertainties in the following areas:

• Further cl arifying t he ch aracteristics a nd d ifferences o f cr eep processes unde r t ensile an d compressive loads

• Analysing the conditions near the edges of the slab in more detail • Consulting literature about Temperature – Reduction of area functions, collecting and analysing

diagrams about different types of cast steel • Working o ut methods f or t he mathematical de scription o f T emperature – Reduction o f ar ea

functions for the different casting groups • Working out a calculation method for the definition of the critical s train value, depending on

composition, temperature, strain rate and cooling rate • Estimating the value of f parameters in a reliable way

0 2 4 6 8 10 12 140.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

L, a

ccum

ulat

ed d

amag

e

Distance from meniscus level, m

"L1" "L2" "L3"

49

2.3.4 WP4 SIMULATION OF PHASE TRANSFORMATION The main objective was t o d evelop an on-line m odel describing the phenomena of heat t ransfer and phase transformation along the strand including IDS solidification and microstructure model from WP3. This co upled m odel p ackage wi ll b e u sed t o d etermine i mportant f eatures an d safety r anges f or t he quality control in WP5 and WP6. Task 4.1 Development of the 3D heat transfer and phase transformation model (TKK) AALTO has an i n-house s oftware s et f or s imulating h eat t ransfer i n c ontinuous cas ting: IDS+ADC, Tempsimu and CastManager. Solidification model IDS and its development was described in Task 3.6. Among others, IDS calculates thermophysical material data needed for heat t ransfer s imulation. ADC model s imulates austenite decomposition during cooling. Tempsimu is a 3 D steady-state heat t ransfer model wh ereas C astManager i s a d ynamic 3 D h eat t ransfer m odel. In th is ta sk, AALTO has further developed ADC, Tempsimu and CastManager models. In the following are descriptions of the models. ADC i s a s emi-empirical s olid-state p hase t ransformation m odule f or s teels within I DS m odel. It simulates t he au stenite decomposition p rocess b elow 1 000°C. I n t he cas e o f l ow-alloyed s teels, th e simulation involves the formation of pro-eutectoid ferrite, pro-eutectoid cementite, pearlite, bainite and martensite, an d i n t he cas e o f s tainless s teels, t he f ormation o f martensite o nly. T he ADC m odule applies a thermodynamic substitutional solution and magnetic ordering model, a carbon diffusion model and special regression formulas based on CCT experiments. The simulation takes into account the effect of s olutes C , S i, M n, C r, M o an d Ni , cooling r ate an d au stenite g rain size. T he A DC m odule al so calculates temperatures Ae3 and Acm taking into account the effect of the 18 solutes of IDS simulation mentioned in Task 3.6 Tempsimu is a t hree-dimensional, s teady-state heat t ransfer model (FEM) for continuous casting. The model cal culates s trand t emperatures i n each n ode o f t he m esh. L iquidus an d s olidus t emperature isotherms ar e al so o btained. T he d ata o f t he cas ter n eeded f or t he m odel ar e: t he m ould s ize, cas ter configuration as t he l ocations o f t he n ozzles an d r ollers. T hermophysical material d ata ( enthalpy, thermal conductivity and density, as a f unction of temperature) are obtained from IDS model. Finally the casting parameters; casting speed, water flow rates for the cooling zones and, mould heat t ransfer from the mould are given. Tempsimu has different boundary condition options to choose from. In the most precise option heat transfer coefficients are used as boundary conditions and they are determined separately for the rollers, nozzles and the areas between them. CastManager is a d ynamic 3D heat t ransfer model (FDM) for continuous casting which has a s pecial module f or cal culating t he mould h eat transfer. C astManager cal culates s trand temperatures i n each mesh n odes, f or e xample i n t he co rners, t oo. T he m odel i s al so an o n-line model d ue to its f ast calculations al goritms. TEMPSIMU model i s n eeded for s etting u p t he cas ter, i ts geometry, n ozzles, rolls, cooling zones and water intensity curves of the nozzles. CastManager uses directly process data from the caster CastManager consists of the s imulator and the player mode, where the s imulated cast can be studied off-line. Model developments in this project Austenite decomposition module ADC (from IDS) has been under an intensive development. A large amount o f C CT d iagrams f rom l iterature an d a C D cal led “CD D atabase o f s teel tr ansformation diagrams”, (compilation by Henrik K aker) c ontaining h undreds o f CCT ( and T TT) ex perimental diagrams, has been purchased. Getting the phase transformation curves into the numeric form has been conducted with digitising software (WINDIG, available freely on internet). This digitising is very time-consuming a nd ha s t o be m ade with ca re. M ore d iagrams c ontaining t he ab ove m entioned ex isting chemical el ements, as wel l as d iagrams, wh ich al so co ntain n ew el ements, h ave b een d igitised. The CCT d iagrams in n umerical f orm a nd its r elating d ata: s teel composition, a ustenitising te mperature,

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austenitising tim e h as b een m odelled w ith s tatistical m ethods. This d evelopment wi dens t he s teel composition ranges and improves the accuracy of calculating the phase transformations. Tempsimu: Improved he at t ransfer c oefficient bo undary c onditions al lowing f or f lexible s econdary cooling wat er d istribution d istribution a nd wat er f low r ates, wh en t here ar e s eparate wat er f low r ate controls in width direction. CastManager: IDS and ADC models were coupled to CastManager. Thermophysical material properties; enthalpy, thermal conductivity and density are obtained as a function of temperature from IDS and ADC. Coupling enables the calculation of phase regions and phase f ractions dur ing on-line simulation of real cast. On-line simulator CastManager In Figure 4-1 a-d are shown different user interfaces and the results and process data which is needed for simulation. In the following descriptions of the Figure: Figure 4-1 a) The main user interface window: from left to right: Surface temperatures, isotherms (for example l iquidus a nd s olidus), s econdary c ooling w ater a mounts pe r z one. O n the ut most r ight: t he momentary cas ting p arameters: d ate, h eat, t ime, cas ting s peed, cr ater en d ( =liquid p ool) et c. an d calculated values: liquidus and solidus isotherms in the cast strand (picture also in the middle of the user interface, as mentioned), measured and calculated mould heat transfer. Figure 4-1 b) Process data needed for the on-line calculation. Figure 4-1 c) The user interface window: Phase fractions at a certain moment during casting, here from left to right: liquid, delta ferrite and austenite. Figure 4 -1 d) The u ser i nterface w indow: Phase r egions i n t he s trand a t a c ertain m oment dur ing casting.

Process data for casting simulator

Date [dd.mm.yyyy]

Time [hh:mm:ss]

Heat no. [NNNNNN]

Steel grade [SSSSSS]

Ladle weight [tons]

Tundish weight [tons]

Casting temperature [°C]

Mould heat transfer [kW]

Casting speed [m/min]

Secondary cooling waters in each X-side [m3/h]

Y-side [m3/h]

a) b)

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c) d)

Figure 4-1. CastManager results in different user interfaces and process data for the simulation.

These further developed and coupled models here in Task 4.1 and Task 3.6 will be utilised as an on-line casting s imulator in WP5 a nd WP6 f or th e q uality p rediction a s th e c ritical c asting p arameters and safety ranges for them have been determined for controlling as-cast quality. A general view of the on-line co upled s ystem i s p resented i n F igure 4 -2. Thermophysical m aterial d ata as a f unction o f temperature needed for heat transfer simulation comes from IDS and phases and phase fractions along cast s trand during c asting f rom bo th I DS a nd ADC. At t he m oment there ar e c onstant co oling r ates (1°C/s fo r s olidification a nd 0. 1°C/s for a ustenite de composition f or pha se a nd phase f raction calculations in th e s trand but th is does it d o n ot a ffect much th e r esults a s cooling r ates a re s low in casting. Quality indices (descriptions in Task 5.5) are not yet directly coupled to the casting simulator, but this is planned to be done in the near future. Now the indices will be used off-line.

52

Figure 4-2. On-line simulator construction for quality prediction of the cast strands.

IDS (+ADC)

CastManager

Process data

Output data

Quality prediction

On-line casting simulator CastManager

Quality indices from IDS and ADC

(off-line)

Material data temperature dependent

Phases and phase fractions

53

2.3.5 WP5 MODEL APPLICATION AND VALIDATION IN STEADY-STATE CONDITION The objective of this work package was to produce experimental data from casting trials and to use the models de veloped i n W P2, WP3, W P4 t o s imulate c asting c onditions c orresponding t o t hese t rials. Also calibration of the models and definition of safety ranges for the critical features defined in other work packages will be performed. Task 5.1 Adaptation of caster plants (DUFERCO, CAS, DUNAFERR) CAS has machined and prepared caster moulds to perform experimental trials on 160*160mm2 square billet casting. Figure 5-1 shows the instrumented mould and the scheme relevant to the thermocouples positioning. The t hermocouple di stribution a llows t o s tudy i n de tail t he c ombined e ffects on t he i n-mould f luid-dynamics of the 5-holes nozzle and of the mould s tirrer, mainly in terms of shell surface temperature and shell growth uniformity. As a matter of fact, multi-hole SEN ensures good liquid metal feeding at meniscus, but waves could occur for high steel velocities in function of the hot-spot occurrence [24].

c

Figure 5-1. Top view (a) and side view (b) of the CAS instrumented mould. c) Thermocouples positioning. (“intradosso” = inner or loose side; “estradosso” = outer or fixed side; “lato” = side).

The thermocouple arrangement has been set in order to have information on the occurrence of uneven heat transfer between shell and mould along the perimeter and along the distance from the meniscus up to the heat flux between the shell and the mould. At DUNAFERR thermocouples wer e i nstalled i n f our m oulds t o ch eck t he t hermal p rocesses, t he temperature di stribution a nd he at t ransfer dur ing continuous c asting. E ach m ould c ontains 24 thermocouples, their arrangement on one side of a mould is shown in Figure 5-2. The copper moulds were coated by nickel to decrease the number of the surface cracks. A new l ine scanner was put into operation to measure the surface temperature of the cast s trands. The measured data are s tored in the database of the process control system. Based on the measured values the temperature distribution of the mould can be monitored and the heat flux can be calculated (see Figure 5-3). These calculations were carried out using a FEM model and an inverse heat transfer m ethod. As a result o f t he ad aption o f t he casters DUNAFERR now h as t wo moulds for 800-1300 mm strand width and two moulds for 1400-1500 mm strand width equipped with

54

thermocouples. The Ni coating o f t he m ould s urfaces r educed the appearance o f s lab surface q uality problems.

Figure 5-2. Mould at DUNAFERR equipped with thermocouples (wide side).

Figure 5-3. Calculated heat flux values for the right part of a wide side of the mould.

Within th is p roject DUFERCO installed a n automatic mould powder f eeding system. In a ddition, oscillator has been checked and re-aligned before the project. Surface level in the mould If an entire coil is controlled the results of the up-settings test are not constant. A possible cause for this is the variation of melt level in the mould during casting. Radical variation can cause some defects on the billet (bleeding, powder entrapment, irregular oscillation marks etc.). Figure 5-4 shows some melt level variation in one cast l ine during one sequence and surface quality index of b illets determined in Table 5-1.

Figure 5-4. An example of melt level variation in a mould during casting.

55

The severity of this quality index of is set up according the rules mentioned in Table 5-1.

Table 5-1. Surface quality index determined melt level

Surface q uality in dex, m ean v elocity with its s tandard deviation a nd id entification is a utomatically reported. To follow and measure this index traceability of the billet is assured by identifying the billet before rolling with billet marking. In that way a correlation with the defects on wire and the process of the billet can be made. Casting experiments at CAS CAST T RIALS - CAS has performed cast t rials with the instrumented mould described in Task 5 .1. (installed b y CSM staff). T he e xperimental d ata s hown here refer t o t he s teel F304L1, wi th cas ting speed 1 .5m/min, an d a cal culated ( from wat er t emperature m easurement) average h eat f lux of 1.69MW/m2. Figures 5-5 show the temperature profiles achieved along two adjacent section levels. DATA A CQUISITION - A r easonable q ualitative d istribution i s a chieved in b oth c ases, w ith thermocouples at face centres being ‘hotter’, and the corner ‘colder’. This aspect can be amplified by the t ypical nozzle geometry, wi th four l ateral holes (together with a bottom hole) (see Figure A -2 in Appendix) with the impact stream coming from the nozzle hits directly the mould sides. Examples of thermocouple average measurements are given in Figure 5-6.

SAMPLE COLLECTION F OR M ICROSTRUCTURAL A NALYSIS - Sample co llection h as b een carried out by CAS both on as-cast billets and on rolled products to assess the presence of defects. The ghost line defect class has been investigated, consisting on dark lines at some depth below the surface [25] on the macro-etched sections of cast billets, mainly corresponding to the secondary cooling region. The darkness of the l ine reveals the segregation of some al loy elements. Sub-surface cracks can open [26] at steel grain boundaries from the ghost line during primary and secondary cooling because of the hot-tearing (triggered by the stress dynamics). Furthermore, sub-surface cracks can open up to surface during subsequent plastic deformations.

1. DEFINITION: • Arbitrary index to assess the surface quality of billets

2. SAMPLING: • - For each billet (start and finish is defined by the cutting time) • - Signal level variation (from start to f inish the level variations

induced by cutting are not measured) • - Each ½ second

3. ARBITRARY INDEX 4. THRESHOLDS:

• INDEX 0 when 99 % the variation of level ≤ 3%; • INDEX 1 when ≥ 1 % the variation of level >3%; • INDEX 2 when ≥ 1 % the variation of level > 5%; • INDEX 3 when ≥ 1 % the variation of level > 10 %;

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a) b)

Figure 5-5. a) Distribution of the thermocouples at 120mm from meniscus and the corresponding temperature time evolution. ). Distribution of the thermocouples at 180mm from meniscus and the corresponding

temperature time evolution.

Figure 5-6. 160*160mm2 mould thermocouple signals from F304L1 heats (left) and 420A7 heats (right). Table 5-2 shows the list of the heats interested in this analysis and the main casting parameters.

Table 5-2. Steel CAS F304L1 - Main casting parameters, common (on average) to all the heats considered.

steel casting speed

[m/min]

tundish weight [ton]

water flux rate [m3/h]

zone x1 zone y1 zone x2 zone y2 zone x3 zone y3

F304L1 1.5 16 0.8-1.0 0.8-1.0 0.9-1.1 0.9-1.1 0.6-0.8 0.6-0.8

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Figure 5-7 shows the etched surface of the billet samples (HCl diluted / 20min).

Figure 5-7. CAS steel sizes 160*160mm2 a) steel F304L1: absence of observed defects; b) steel 420A7: red-evidenced defects in the off-corner regions.

STEEL F304L1 C AST B ILLETS - The s teel F304L1 c ast bi llets s hows no s ub-surface d efects; the solidification structure is completely columnar from the surface to the billet centre. STEEL F304L1 R ODS - The r ods h ave b een i nspected at t he o ptical m icroscope t o s earch d efects. Straight longitudinal (SL) defects have been observed on steel F304L1 heat 72887 (Figure 5-8): 5 of 13 rods are affected; the defects are 0.08-0.15 mm deep and distributed irregularly in different locations.

Figure 5-8. Steel CAS F304L1, heat 72887: a) surface straight-longitudinal defect; its depth is 0.08-0.15mm; not continuous; rods affected 5/13; b) locations on the rods.

STEEL 420A7 CAST BILLETS - Contrary to s teel F304L1, s teel grade 420A7 of s ize 160*160mm2 show s ubsurface cr acks, m ainly located i n t he o ff-corner r egion, s eldom i n t he m iddle o f t he s ide (Figure 5-9). On average, the distance of the cracks from the external surface is 14-15mm. The external chill zone is not evident while the white band generated by the final s tirrer is well visible. Five heats have been considered: 872971, 972463, 72034, 72622 and 73012. Typical main casting parameters of the heats are listed in Table 5-3.

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Figure 5-9. Typical internal crack in billets of martensitic peritectic resulphurised 420A steel.

Table 5-3. Steel CAS 420A7 – Main casting parameters, commons (on average) to all the heats considered.

steel casting speed

[m/min]

tundish weight [ton]

water flux rate [m3/h]

zone x1 zone y1 zone x2 zone y2 zone x3 zone y3

420A7 1.4 16 0.5-0.7 0.5-0.7 0.6-0.8 0.6-0.8 0.4-0.6 0.4-0.6

In the Tables A-4 - A-8 (in Appendix), CAS has reported data about “ghost line” defect class on the heats considered: casting l ine id., bi llet slice id. inspected, the amount of defects s ites found and the corresponding maximum depth, severity and position from the edge. STEEL 420A7 RODS - Straight longitudinal defects have been observed in all the steel 420A7 rods; they are of two types (Figure 5-10), the type 1 is 0.08-0.09 mm deep, the type 2 is max 0.35 mm deep; both of these types are distributed not continuously in different locations. Surface cracks have been observed in the rolled rods for both steels but with a higher incidence for steel 420A7 than for s teel F304L1, which could be a f irst confirmation of the derivation of some of these defects from the sub-surface cracks previously open in the billets.

Figure 5-10. Steel CAS 420A7 heat 073012: surface straight-longitudinal defect; its depth is 0.08-0.09mm (type 1) and 0.35mm max (type 2); not continuous; rods affected 4/4.

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DUNAFERR carried o ut cas t t rials t o s tudy t he ef fects o f p rocess p arameters o n t he centreline segregation and on the surface quality. All important process data were recorded for the validation of the mathematical models. Thin cross-sections were cut from the selected s labs for further macro- and microstructural investigations. During sample collection the surface quality of the slabs was inspected. Two typical slab defects found are shown in Figure 5-11.

Figure 5-11. Typical surface defects at DUNAFERR a) transverse crack, b) star crack.

As a result of the cast trials a large variety of slab samples was available with known casting parameters for f urther microstructural i nvestigations. It c an b e s tated t hat t he Ni co ating greatly d ecreased t he surface quality problems of the slabs. The number and the size of the star cracks were much smaller on the surface of the s labs as a result of the Ni coating (see Table 5-4.). Evaluating the collected data it became possible to demonstrate the e ffect of superheat and cas ting speed modification on the mould temperature di stribution a nd o n t he s trand s urface t emperature. Figure 5-12 s hows t he ef fect of superheat on the surface temperature of the strands measured by line-scanner.

Table 5-4. Comparison of surface defects on slabs cast in the moulds with and without Ni-coating.

Figure 5-12. The effect of superheat on the surface temperature of the strand.

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Cast trials at DUFERCO Main f eatures of DUFERCO billet ca ster h ave b een c ollected an d r eported t o allow t he m odel simulation planned in this research project. DUFERCO performed specific analysis focused to improve the surface quality. The main defects in the chosen s teel g rades h ave b een i dentified b y d ifferent ap proaches: t heoretical point o f view, visual inspection o f b illet surface an d m etallographic ex amination. T he cr itical d efects f or ap plications o f cold-heading steels have been identified as well as the promising casting practices. Defects which are critical for cold-heading applications are:

• Depressions • Bleeding • Mini break-out • Craze cracks • Pin-holes (also with high carbon steel grade)

1.Critical Steel Grades: cold-headed steels (C-Mn-B-Ti) DUFERCO focused in this project on critical cold heading grades C-Mn-B-Ti, mainly on 20MnB4 and 30MnB4. Other steel grades belonging into this critical group steels were 19MnB4, 23MnB4. Defect mechanism: In these grades a coarse austenite grain grows at the surface. The presence of high level of nitrogen, aluminium, boron induces a low hot ductility at bending point of caster resulting in transversal cracks in the billet corners. The wire rod is characterised by high density of laps and poor rate of up-setting test. In Table 5-5 two heats were chosen for an example of the secondary cooling effect on defects. Casting parameters and calculated Ferrite potential (Task 5.5) values are given in Table 5-6. Typical defect on billet and its evolution in wire rods is in shown in Figure 5-13.

Table 5-5. Steel compositions of example heats 41334 and 69469 in C-Mn-B-Ti steel grade.

Table 5-6. Casting parameters of heats 41334 and 69469 of steel grade C-Mn-B-Ti and calculated Ferrite potential (FP) values.

Heat C Mn S P Si Cu Al Ca Ni Cr Mo N B Ti 69469 0.20 0.93 0.006 0.011 0.048 0.053 0.028 0.002 0.042 0.24 0.007 0.0082 0.0003 0.027 41334 0.20 0.93 0.002 0.011 0.06 0.061 0.035 0.001 0.048 0.058 0.01 0.0088 0.0003 0.035

CP FP Heat Grade 0.20 0.76 69469 23MnB4 0.21 0.72 41334 19MnB4

Superheat ΔT 35 °C Speed vc 2.3 m/min

Frequency f 150 c/min Stroke 8 mm Taper convex 0-700 t

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a) b) c)

Figure 5-13. Evolution of defect: a) billet surface edge, b) cross section (billet) c) wire rod (cross section). Operational countermeasure: A m ethod o f p reventing a t ransverse cr acks i s t o av oid a b rittle temperature r ange at b ending an d straightening. T he ch anges o f t he s econdary c ooling p attern ( to increase bending temperature > 950°C at corners from menu C to menu H was adopted (Table 5-7). This new operational p ractice has been applied wi th good results in t erms of up-setting rate test. But this pattern of secondary cooling induce the craze cracking when the steel contains high level of tramp elements as (Cu, Sn, As). Surface temperature was low enough that AlN was not formed avoiding i ts effect on lowering ductility.

Table 5-7 Secondary cooling menu C and H of DUFERCO (casting speed 2.2 m/min).

The co ld h eaded steels are hi gh a dded v alue qua lity grades a nd n o cr acks ar e allowed o n t he f inal product. DUFERCO modified s craps menu, s et t he m aximum a ge o f 1000 t ons for mou ld and decreased secondary c ooling b y changing i ts secondary c ooling menu f rom C to H (Table 5-7). Al so grinding was i ncreased i nto 4 f aces of each b illet an d ad ditional cu ts ar e made at t he wi re rod mill. Macroetched samples in Figure 5-14 show the impact of secondary cooling (menu C vs. H) on internal quality o f th e b illet ( 23MnB4). After t hese above m entioned modifications, th e q uality of th e c old-headed wire rods raised up: up-setting test of good quality increased from 81% to 95%.

Heat 69469 (menu C) Heat 45679 (menu H) Heat 45680 (menu H)

Figure 5-14. Macroetched billet samples with cooling menu C and H.

Cooling menu C zone W [l/min] W [m³/h] p [bar] [l/kg] Z0 158 9.50 2.91 0.46 Z1 128 7.70 1.24 0.37 Z2 97 5.80 1.66 0.28

Cooling menu H zone W [l/min] W [m³/h] p [bar] [l/kg] Z0 112 6.72 1.46 0.33 Z1 110 6.60 0.91 0.32 Z2 80 4.80 1.13 0.23

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Additionally some slices of bi llets of 19MnB4 grade were cu t on wh ich corner cracks could be seen (Figure 5-15) (cooling menu H ). Th ree samples wer e i nvestigated, f rom l eft: near t he co rner wi th cracks, near the c orner wi th deep oscillation marks, and one in the middle face wi th deep oscillation mark. A regular structure of solidification without any major perturbation can be seen on macroetched sample (Bechet-Beaujard etching). The solidification horn is almost non-existent despite the presence of high depression on the sample 503702-1. In SEM in vestigations only iron oxides were ch aracterised from the cracks. (Figures 5-16 and 5-17).

Figure 5-15. Macroetched billets of steel grade 19MnB4 (cooling menu H).

Figure 5-16. SEM investigations on cracks over 10 mm on billet surfaces in steel grade 19MnB4.

63

Figure 5-17. SEM investigations on cracks over 3 mm on billet surfaces in steel grade 19MnB4.

With these C-Mn-B-Ti steels decreasing the amount of water in the secondary cooling have had benefit on the surface quality but for some grades, for example for the grade 20MnB4 (for chain applications), cooling menu H (Table 5-17) has not been enough. A new cooling menus J (0.83 l/kg at 2.2 m/min) was tested. Each billet was rolled after grinding the corner and controlled. The rejection rate of wire rods due to surface defect changed from one heat to another. Table 5-8 summarises the casting operation and quality of the steel grade 20MnB4 at DUFERCO. Casting parameters (cooling, casting speed, mould powder etc.) were adapted as a result of quality improvements (lower rejection percentage of wire rods).

64

Table 5-8. A summary of the casting operation and quality of the steel grade 20MnB4 at DUFERCO.

In the end of 2011 DUFERCO produced 30MnB4 grade. To check the quality the billets were ground after casting and up-settings tests were made on head and tail of each coil. Each coil with a bad result was r ejected. T able 5-9 shows a s ummary of t he cas ting operations an d q uality of t he s teel g rade 30MnB4.

date

Sequ

ence

nr.

Mol

d Po

wde

r

mol

d flo

w (m

³/s)

heat

nr.

FP Cueq

# ac

tive

lines

spee

d (m

/min

)

cool

ing

men

u

supe

rhea

t

inde

x of

the

leve

l of

stee

l in th

e m

old

tons

pro

duce

d

% o

f disc

ard

53187 0.732 0.105 5 1.9 H 46 0.875 90.56 5.1653185 0.709 0.158 5 2.2 H 27 0.725 86.395 22.1

53186.1 0.781 0.158 5 2.3 H 21 0.886 75.596 27.0153188 0.742 0.060 5 2.3 H 41 0.5 86.395 15.7453189 0.759 0.060 5 2.3 H 16 0.571 75.356 5.8254372 0.756 0.045 6 2.1 H 47 1.347 100.346 11.7954373 0.813 0.053 6 2.3 H 30 1.125 98.298 17.4454374 0.734 0.079 6 2.3 J 23 1.089 92.155 38.3754375 0.755 0.058 6 2.3 J 29 1.13 94.203 054793 0.728 0.047 6 1.9 H 49 1.381 86.011 2.3354794 0.757 0.078 6 2.2 H 31 1.583 98.298 12.2154795 0.74 0.073 6 2.3 H 31 1.419 88.059 3.0554796 0.752 0.048 6 2.2 H 36 1.375 98.298 12.5454797 0.749 0.049 6 2.2 H 30 1.34 96.251 14.4454798 0.778 0.069 6 2.3 H 33 1.024 86.011 2.1755134 0.764 0.041 5 2.2 H 36 0.975 91.915 055135 0.745 0.054 5 2.3 H 27 0.814 88.059 4.6555136 0.716 0.045 4 2.3 H 28 0.705 96.443 055665 0.769 0.084 6 1.7 J 56 0.917 86.011 055664 0.723 0.054 6 2 J 33 0.833 98.298 3.7655666 0.753 0.081 6 2 J 20 1.122 100.346 7.5255667 0.751 0.072 6 2 J 18 1.195 83.963 055773 0.756 0.087 6 2 J 50 0.542 93.691 055774 0.715 0.102 6 2 J 41 0.5 105.69 055775 0.743 0.080 6 2 J 29 0.553 91.739 055776 0.767 0.073 6 2 J 27 0.564 76.124 1.9556317 0.793 0.098 6 1.8 H 56 0.604 98.298 14.1456318 0.787 0.108 6 2 H 43 0.786 86.011 2.3356319 0.751 0.000 6 2 H 33 0.767 88.059 056320 0.75 0.104 6 2 H 22 0.683 83.963 056321 0.738 0.089 6 2 H 32 0.827 106.49 7.5156509 0.776 0.107 6 1.8 J 48 0.395 88.059 12.8556510 0.728 0.069 5 2 J 37 0.2 92.155 14.8656511 0.789 0.054 5 2.05 J 22 0.175 81.915 14.6556512 0.768 0.076 5 2.1 J 18 0.239 94.203 3.91

28.10.2011 17204 SYNTHERM GB 1022/M 78

12.11.2011 17227 SYNTHERM GB 1022/M 80

29.8.2011 17147 SYNTHERM GB 1022/M 80

3.9.2011 17153 SYNTHERM GB 1022/M 80

20.6.2011 17074 Melubir 3011 80

5.7.2011 17101 Melubir 3011 80

10.4.2011 16957 Melubir 3011 81

1.6.2011 17045 Melubir 3011 82

65

Table 5-9. A summary of the casting operations and quality of the steel grade 30MnB4.

2. Critical Steel Grade C10 (C-Mn-Ti peritectic steel) C-Mn-Ti is the second critical steel grade group which DUFERCO investigated in this project (Tables 5-10 and 5-11). The surface of this grade is characterised by a coarse austenite grain size. High level of nitrogen induces a rich AlN precipitation along the grain boundaries. Under a low strain rate at bending point of caster the surface is subjected to embrittlement along the austenite grain boundary (hot ductility of this steel deteriorates). The first countermeasure of preventing a transverse cracks was to avoid a b rittle temperature range at bending and straightening of the billets. Up-setting test rate of the wire rod was improved by increasing secondary cooling from menu C (1.11 l/kg) to menu A (1.22 l/kg) (Table 5 -12). Cracks in the billets with the secondary cooling menu C are shown in Figure 5-18. New concept for transverse crack prevention The hot ductility can be improved by rapid cooling until the δ + γ phase region and reheating up to δ region. This thermal history is able to produce a layer with idiomorphic ferrite. By avoiding the ferrite-like film (ferrite along austenite grain boundary) hot ductility of the steel grade is improved. At the exit of m ould i t i s possible t o produce a t hickness o f 0. 5-2 m m o vercooled b y S SC ( Surface S tructure Control) (from 1080° C t o 800° C w ith cooling rate a bout 7° C/s) us ing a hi gh w ater f low r ate a fter natural reheating to 950°C.

Table 5-10. An example composition of peritectic C-Mn-Ti steel grade.

C Mn S P Si Cu Al Ca Ni Cr Mo N Ti 0.092 0.44 0.008 0.014 0.025 0.061 0.031 0.002 0.044 0.056 0.007 0.008 0.017

date

Sequ

ence

nr.

Mol

d Po

wde

r

mol

d flo

w (m

³/s)

heat

nr.

FP Cueq

# ac

tive

lines

spee

d (m

/min

)

cool

ing

men

u

supe

rhea

t

inde

x of

the

leve

l of

stee

l in th

e m

old

tons

pro

duce

d

% o

f disc

ard

56463 0.52 0.031 6 1.8 J 59 0.667 92 1056462 0.498 0.049 6 2 J 41 0.381 92 11.956464 0.555 0.027 6 2 J 39 0.455 83.3 6.156705 0.484 0.05 6 1.8 J 50 0.786 92 056706 0.502 0.036 6 2 J 46 0.708 105.2 056707 0.479 0.042 6 2 J 36 0.683 89.856708 0.498 0.043 6 2 J 36 0.692 87.6 5

10.11.2011 17221 SYNTHERM GB 1022/M 80

7.12.2011 17263 SYNTHERM GB 1022/M 81

66

Table 5-11. Casting parameters of C-Mn-Ti grade and calculated Ferrite potential (FP).

Table 5-12. Secondary cooling menus C and A of DUFERCO (casting speed 2.2 m/min).

Figure 5-18. Cracks on the C-Mn-Ti grade billets with the secondary cooling menu C. 3.Critical Steel Grade C72D2 (high carbon steel) The third critical steel group investigated at DUFERCO was high carbon steels. The secondary cooling pattern of high carbon steel grade (C > 0.70) was performed by hard cooling. This cooling pattern is aimed t o ach ieve a s trand wi th a mushy z one b etween 2 5-35% a t the final s tirring z one. T his operational r equirement a llows m inimising th e s egregation f or h igh d iameter w ire r od. In o rder t o improve the steel quality DUFERCO increased remarkably the water flow rate from 0 .37 l /kg (menu C) to 1.20 l/kg (menu F) at the second cooling zone, zone Z1. The compositions of the trial heats are shown in Table 5-13. Heat 68910 was cooled according to menu C and heat 64958 with menu F (Table 5-14). Hard cooling at the caster and a macroetch cross-section of a billet are in Figure 5-19. As a result

CP FP Heat Grade 0.09 1.02

Superheat ΔT 35 °C Speed Vc 2.3 m/min

Frequency F 150 c/min Stroke 8 mm

Taper Convex 0-700 t

Cooling menu C zone W [l/min] W [m³/h] p [bar] [l/kg] Z0 158 9.50 2.91 0.46 Z1 128 7.70 1.24 0.37 Z2 97 5.80 1.66 0.28

Cooling menu A zone W [l/min] W [m³/h] p [bar] [l/kg] Z0 175 10.50 3.6 0.51 Z1 150 9.00 1.7 0.43 Z2 97 5.80 1.7 0.28

67

from a dapting t he c ooling m enu F , t he s egregation i ndex w as i mproved, which can b e obs erved i n Table 5-15.

Table 5-13. Composition of the heat with hard cooling (68910) and the heat without hard cooling (64958).

Heat C Mn S P Si Cu Al Ni Cr Mo N Cooling 68910 0.84 0.74 0.007 0.015 0.29 0.043 0.050 0.032 0.22 0.006 0.0075 menu F 64958 0.83 0.73 0.002 0.010 0.29 0.051 0.034 0.040 0.21 0.005 0.0067 menu C

Table 5-14. Secondary cooling menu C and F of DUFERCO (casting speed 2.2 m/min).

Figure 5-19. a) Hard cooling in zone Z1 and b) Macroetched cross-section of a billet (menu F).

Table 5-15. Segregation index of billet specimens of heats 68910 and 64958 and the reduction of area, Z %, of

wire rod (diameter 13 mm). Segregation index: 1 = the best, 3 = the worst), Z (%) = ROA, reduction of area.

Test heat 1 2 3 4 5 6 7 8 9 10 Z (%)

68910 1 1 1 2 2 1 1 2 1 1 32 64958 3 3 3 3 2 3 3 3 2 2 28

Cooling menu C zone W [l/min] W [m³/h] p [bar] [l/kg] Z0 158 9.50 2.9 0.46 Z1 128 7.70 1.2 0.37 Z2 97 5.80 1.7 0.28

Cooling menu F zone W [l/min] W [m³/h] p [bar] [l/kg] Z0 183 11.00 3.9 0.53 Z1 417 25.00 13.0 1.20 Z2 97 5.80 1.7 0.28

68

Task 5.3 Execution of microstructural analyses (DUNAFERR, CSM) CSM have performed microstructural analyses on samples of CAS. An example of a sample is shown in Figure 5-20. Scanning Electron Microscope observations have been made on billet pieces by CSM (Figure 5-21).

Figure 5-20. Example of billet section from which samples were derived for EDS analysis.

Figure 5-21. An example of CSM EDS analysis of CAS samples of steel F304L1.

The investigation performed on the samples indicated the p resence of powder i n the macro-inclusion agglomerate found. The related spectra show the presence of typical elements (e.g., Na) associated to powder composition.

69

The indications have confirmed the tendency of such steel - within the operating conditions examined - to b e p rone to p owder s ticking. C ross-correlating the samples and the heat h istory, the occurrence of such a defect has been correlated to improper powder melting at start of casting. It h as been suggested t o f ind po wders w ith ‘ improved’ c omposition, i n o rder t o f avour t he r apid formation of a reliable liquid pool. It has given further elements for validating the models and finding correlations between melted powder amounts and heat transfer in the mould/steel gap. DUNAFERR analysed t he cen treline s egregation of s everal s labs o f d ifferent c hemical co mposition because centreline segregation is a critical point regarding the slab quality. The macrosegregation of the slabs was characterized by Baumann imprint and macroetching by ammonium persulphate solution. In some cas es at t he cen tral zone o f t he s labs ch emical composition was measured as a f unction o f t he distance from the centreline. To characterise the porosity of the centreline of the slabs ultrasonic and x-ray investigations were carried out on some samples. A systematic examination of metallographic methods for detection of primary steel texture was carried out, b ecause i n s pite o f fast development o f t echnical t ools f or ex amination, t he i mportance of traditional macrostructural i nvestigation h as n ot d ecreased; on t he contrary, t hese methods ar e i n t he state o f t heir r evival. On e o f ev ident r easons f or i t i s t he f act, that t he r esults o f m acrostructural examinations and the conclusions drawn f rom them are in the closest relation w ith the parameters o f casting technology, reflect their changes and the deviations from the specified values. During t he m icrostructural an alyses of t he co llected s amples DUNAFERR focused on t he s tudy of centreline segregation since segregation can still cause quality problems at some steel grades. A typical Baumann print is shown in Figure 5-22. Centreline segregation was compared in s labs and in 40 mm thick hot plates to investigate the effect of hot rolling on the segregation. It was found that the nature of the segregation did not change during hot rolling and if significant centreline segregation is present in the slab then it can cause quality problem in the hot rolled plates and strips as well. Chemical analyses were carried out to quantitatively characterise centreline segregation (see Figure 5-23). Our ex periments t o ch aracterise t he por osity of t he centreline o f th e s labs b y u ltrasonic o r x -ray methods d id n ot g ive b etter r esults th an th e tr aditional m etallographic te chnique. The r esults o f th e microstructural characterisation were used during validation of the mathematical models.

Figure 5-22. Baumann print of the slab cross-section.

Figure 5-23. Chemical composition as the function of the distance from centreline.The background is the Baumann print of the investigated slab.

70

Task 5.4 Calibration of the models (BFI, CSM, DUNAFERR, AALTO) Calibration o f t he num erical m odel f rom WP2 a nd WP3 a ccording t o relevant i ndustrial da ta a nd collected b oundary c onditions f or one cas t t rail was u ndertaken b y BFI. T he t hermal bo undary conditions f or t he num erical c omputations w here a dapted t o t he c ontinuous s lab cas ter d ata. From temperature measurements conducted by DUNAFERR in WP5 a circumferential average of the mould temperature was evaluated in dependence from the mould height. From this temperature distribution a heat transfer coefficient of 6000 W/m²K was defined and a temperature distribution in the mould was computed in good agreement to the measured temperature distribution by DUNAFERR. The general temperature characteristics m easured b y DUNAFERR, s howing a h igher temperature n ear t he meniscus w as i n g ood a ccordance t o t emperature di stributions m easured i n s imilar m oulds f rom t he literature [3,27,28]. With data from the DUNAFERR slab caster and results from computations from OBUDA University for t he s teady s tate caster t rials t he n umerical c omputations wer e cal ibrated. A n e xample f or t he computed temperature distribution along the strand is given in Figure 5-24. Temperatures at the end of the p rimary c ooling zo ne wer e s tated with ap proximately 1000° C a t t he c orner o f t he s lab a nd approximately 1170°C at the mid wide side. At the end of the secondary cooling zone a temperature of approx. 845°C was given from DUNAFERR. The temperatures computed were in good agreement to the data provided by DUNAFERR (Table A-1).

Figure 5-24. Numerically computed temperature distribution at the centreline, narrow side, wide side and

corner of the strand. LIQUID POOL - The definition of a calibration technique for the "Liquid pool model" has been carried out by CSM starting from the basic idea of not using data from the process to calibrate the parameter a of the sinterisation kinetic (see Equation 1), but deriving it from a measurable property of the powder: the melting rate. Once a is determined, the s imulation of the casting process is used to verify the model. Figure 5-25 summarises the calibration procedure flowchart.

71

Figure 5-25. Flowchart of the calibration technique for the "Liquid pool model".

The p owder m elting r ate cu rve (melting r ate vs. C FREE) i s derived b y u sing t he ex perimental d evice shown in Figure 5-26a. Within th is experimental device, a 3m m thick powder l ayer i s put on a S iC plate, heated at 1400°C by a solenoid and the time elapsed until complete melting is measured. At this stage, a s imulation has been carried out to verify the calibration technique previously described and to check the "Liquid pool model" functionality.

The simulation steps have been:

1. Setting the content o f f ree carbon. From t he ex perimental m elting r ate cu rve, both the g of powder to be melt in the experimental device and the total melting time have been identified.

2. Experiment device has been simulated by the "Liquid pool model"; the kinetic parameter a has been cal ibrated recursively, in order to obtain a v oid ratio evolution at the top of the powder layer with a void ratio β ≤ 0.01 at a s imulation time equal to melting time. At the end of the recursive procedure, the calibrated value of kinetic parameter a has been computed (Figure 5-26b).

3. Calculation of the time evolution of the three layers thickness (base state, sintered and liquid) at the meniscus, as shown in Figure 5-27.

As i t can be noticed, the model results poorly agree with the measure. It can be due to the following reasons: In adequate calibration of sinterisation kinetic parameter Simulation of regular additions, instead of real ones Liquid p ool h eight m easures a re in trinsically h ighly s cattered. T hen o ne m easure i s n ot

representative.

72

Figure 5-26.a) Experimental device for the melting rate curve measurement (used in ECSC project 7210.PR/273, June 2004). b) Simulation of the experimental device - Numerical result obtained at the end of

the recursive procedure to calibrate the value of kinetic parameter a

Figure 5-27 - “Liquid pool model” numerical results.

MOULD HE AT F LUX - The c omputed e volution a long t he mould’s he ight of t he he at f lux pr ofile along t he s ection p erimeter i s g raphed i n Figure 5-28. It ha s be en c alibrated t o m ake t he c omputed temperature converge to the measured data at the midface and at the corner (Figure 5-29) for both the steel grades CAS 420A7 and F304L1.

The temperature f ield resulting from 3D thermo-mechanical FEM s imulations of the mould has been compared to the experimental data at the corner and the mid-face regions. A good agreement has been found in both the heats of the steels (Figure 5-30).

73

1

1.5

2

2.5

3

3.5

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

spec

ific

heat

flux

[M

W /

m2]

z = 0m (meniscus) - 420A7z = -0.1m - 420A7z = -0.2m - 420A7z = -0.3m - 420A7z = -0.4m - 420A7z = -0.5m - 420A7z = -0.675m - 420A7

1

1.5

2

2.5

3

3.5

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

spec

ific

heat

flux

[M

W /

m2]

z = 0m (meniscus) - F304L1z = -0.1m - F304L1z = -0.2m - F304L1z = -0.3m - F304L1z = -0.4m - F304L1z = -0.5m - F304L1z = -0.675m - F304L1

mid-face corner

thermocouple vertical lines thermocouple vertical lines

mid-face corner

1

1.5

2

2.5

3

3.5

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

spec

ific

heat

flux

[M

W /

m2]

z = 0m (meniscus) - 420A7z = -0.1m - 420A7z = -0.2m - 420A7z = -0.3m - 420A7z = -0.4m - 420A7z = -0.5m - 420A7z = -0.675m - 420A7

1

1.5

2

2.5

3

3.5

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

spec

ific

heat

flux

[M

W /

m2]

z = 0m (meniscus) - F304L1z = -0.1m - F304L1z = -0.2m - F304L1z = -0.3m - F304L1z = -0.4m - F304L1z = -0.5m - F304L1z = -0.675m - F304L1

mid-face corner

thermocouple vertical lines thermocouple vertical lines

mid-face cornera b

Figure 5-28. Evolution of the heat flux profiles along the casting lines; a) heat 72142-72143 of steel CAS F304L1; b) heat 72299-72300 of steel CAS 420A7.

The computed s tationary temperature field reached by the mould when submitted to the heat flux has been employed as input for computing the mechanical evolution of the mould itself.

Figure 5-29. Agreement of the thermal field between acquisition and computation (FDM model).

30

40

50

60

70

80

90

100

110

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7distance from meniscus [m]

tem

pera

ture

[°C

]

F304L1 - midface - average acquisition F304L1 - midface - computedF304L1 - corner - average acquisition F304L1 - corner - computed420A7 - midface - average acquisition 420A7 - midface - computed420A7 - corner - average acquisition 420A7 - corner - computed

74

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

50 60 70 80 90 100 110 120 130 140 150

temperature at mid-face [°C]

Posi

tion

from

men

iscu

s [m

]

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 10 20 30 40 50 60 70 80 90 100

temperature at corner [°C]

Mid-face - Experimental Mid-face - FEM 3D

20mm from corner - Experimental 20mm from corner - FEM 3D

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

50 60 70 80 90 100 110 120 130 140 150

temperature at mid-face [°C]

Posi

tion

from

men

iscu

s [m

]

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 10 20 30 40 50 60 70 80 90 100

temperature at corner [°C]

Mid-face - Experimental Mid-face - FEM 3D

20mm from corner - Experimental 20mm from corner - FEM 3D

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

50 60 70 80 90 100 110 120 130 140 150

temperature at mid-face [°C]

Posi

tion

from

men

iscu

s [m

]

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 10 20 30 40 50 60 70 80 90 100

temperature at corner [°C]

Mid-face - Experimental Mid-face - FEM 3D

20mm from corner - Experimental 20mm from corner - FEM 3D

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

50 60 70 80 90 100 110 120 130 140 150

temperature at mid-face [°C]

Posi

tion

from

men

iscu

s [m

]

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 10 20 30 40 50 60 70 80 90 100

temperature at corner [°C]

Mid-face - Experimental Mid-face - FEM 3D

20mm from corner - Experimental 20mm from corner - FEM 3D

a b

Figure 5-30. Mould temperature fields at mid-face and 20mm far from the corner. Comparison between the thermocouple acquisition and the results from computation; a) heat of steel CAS F304L1; b) heat of steel CAS

420A7.

Calibration of centreline segregation model (DUNAFERR, OBUDA) OBUDA has ev aluated 7 cas ting t rials p erformed at DUNAFERR. T he t rials an d t he cal culations aimed a t th e c alibration a nd v alidation of c entreline s egregation m odel. T he v alidation b ased o n th e supposed effect of supporting roll gaps on porosity formation and mushy liquid flow in the centre of the slab. This effect plays important role in the last stages of slab solidification according to the results of previous experiences and calculations. In this report the results of only one trial will be discussed. For this industrial trial steel with the following chemical composition was chosen (Table 5-16).

Table 5-16. Chemical composition of the investigated steel.

This heat was cast into two strands on the vertical slab caster of DUNAFERR. The casting parameters of the strands were identical, i.e. the casting rate, the primary and secondary cooling intensities and the superheats were the same. The only difference between the two strands was the setting of the supporting rolls a long t he c asting machine. T he original r oll s etting w as applied f or t he strand no . 1 a nd t he modified setting for the strand no. 2 according to the Figure 5-31.

75

Figure 5-31. Setting of the original and the modified supporting roll gaps along the strand.

The expected porosity and the characteristics of mushy liquid flow were calculated for both strands by LMI – Liquid M otion Intensity m odel. F or th e c entreline o f s labs th e calculated p orosity l evels ar e given i n Figure 5-32. The modification of gaps improved a little b it th e level of c entreline porosity, which decreases the level of centreline segregation.

Figure 5-32. Calculated porosity levels in the case of the original and the modified roll settings.

The other feature of cen treline segregation formation i s the flow rate function of mushy liquid in the mushy part of strand. The flow rate functions are given in Figure 5-33.

76

Figure 5-33. Mushy liquid flow rates in the centreline region with the original and the modified roll settings.

From the viewpoint of centreline segregation the low positive value of flow rate is favourable. In this case the final level of flow rate at about 6 meters (6000 mm in Figure 5-33) from meniscus level (i.e. at the boundary of liquid and mushy centre area) the flow rate becomes lower in the case of modified roll setting, but the maximum value of flow rate inside the mushy part of the strand is higher than in the original case. Taking into account both the calculated porosity and the flow rate a small improvement in centreline segregation can be expected as a r esult of the roll setting modifications. Figure 5-34 shows the centreline segregation in the slabs. The improvement in the segregation level can be clearly seen.

Figure 5-34. Etched cross-sections of the centre area of the cast slabs a) on the left the original taper and b) on the right the modified taper.

Calibration of creep model (DUNAFERR, OBUDA, College of Dunaujvaros) For calculation of stresses and strains in the slab surface and subsurface area mathematical model based on phenomenological equations has been developed (Task 3.7). In order t o calibrate and validate the model, s ix tr ials u nder w ell-defined p arameters wer e p erformed b y Gleeble 3 800 t ype t hermo-mechanical s imulator at College of D unaujvaros. The Gleeble 3 800 g ives th e possibility to p erform creep tests as s train or s tress controlled processes. Among the s ix t rials two were controlled by st ress and i n four cas es s train was t he controlling p arameter. Test material i n al l cas es was as -cast St5 2-3. Before creep tests the heating rate was 10°C/s, soaking time 1 min.

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During t he t wo s tress-controlled tr ials th e c ontrol s ystem w as n ot a ble to stabilise th e s tress le vel, therefore en ormous f luctuations o f t he s tress s ignal wer e d etected. T he ef ficiency of p rocess co ntrol seemed to be much better in strain-controlled cases. All the four trials were successful and gave realistic results. The s tress function compared t o t he cal culated values and the s tress-strain curves proved the reliability of Kozlowski’s no. 2 model [22]. AALTO has previously validated IDS m odel with th e r esults o f m any experiments f rom lite rature performed with steel grades of wide compositional ranges [17-20]. Heat transfer boundary conditions in Tempsimu and CastManager models have been validated with experimental data. In modelling, detailed boundary condition options were used, meaning that heat transfer coefficients were given separately for water sprays, rolls and the area where no water or roll is present, only air convection and radiation as a boundary condition. Values in the Figure 5-35 were used.

Formula for water sprays: h=aWb

h= heat transfer coefficient [kW/m2°C] W=water flow rate [m3/h]

Water-only sprays:a=0.11 and b= 0.64 Water-air sprays: a=0.13 and b= 0.72

Heat transfer coefficient for air convection: 0.02 k / ° Rolls: contact area = 5 mm and temperature 25°C

Solid rolls 0.3 kW/m , internal cooled rolls 1.3 kW/m

Figure 5-35. Heat transfer values used in Tempsimu and CastManager models. Values from experiments in [29-31].

Task 5.5 - Definition of critical variables CSM and CAS has found the following critical issues on steel quality: Fluid-dynamics (criteria for slag entrapment at meniscus) Internal structure/solidification (segregation and hot-tearing)

FLUID-DYNAMICS AT MENISCUS - According to the experience of CSM, there are critical velocity values that result to be risky for some defects occurrence. Above the critical value at meniscus ease the slag-steel emulsification [32]. Above the critical value at hot spot ease the shell ‘washing’, up to break-out risks [33]. INTERNAL STRUCTURE - SEGREGATION - Relationships between segregation index and equiaxed zone are derived from literature [34] as in Figure 5-36. In this way, superheat and segregation index can be related, and the data arising from experimental work of CAS can be fitted to limit the overheat range and to support the overall on-line process model.

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Variation of equiaxed zone with superheat of liquid steel in continuously cast high carbon steel billets.

Variation of maximum degree of centerlinesegregation of carbon with equiaxed zone ratio in high carbon steel billets.

Correlation between segregation index and process parameters via steel internal structure

features

Figure 5-36. Indication of possible correlation between segregation index and process parameters.

INTERNAL STRUCTURE - HOT TEARING - The off-corner of billet is the region between the corner and the point along the billet transverse-section perimeter where the computed gap is minimum; the gap profile de termines a r eduction i n he at f lux g oing f rom m id-face t o t he co rner, r esulting i n a surface temperature peak in the off-corner region, the local shell thinning and the generation of tensile stress in the solidification front. In the solidification front region of the off-corner itself a tensile stress peak is observed: this scenario is a warning for potential defects (Figure 5-37).

Figure 5-37. FEM profiles of interest for identifying the critical parameters.

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With respect to this mechanism of defect formation, a critical parameter can be identified in the heat flux profile derived from the temperatures measured in the mould. Steel F 304L1 - The s teel F 304L1 r esists th e s tresses i nduced by th e s olidification, r esulting in th e absence of observed defects (Figure 5-8a in Task 5.2). Steel 420A7 - To verify the mechanism identified with the analysis performed on steel F304L1, further analyses on steel 420A7 have been performed with the aim of confirming that the mechanism is able to induce defects observed in different steel classes (Figure 5-8b in Task 5.2). Task 5.5 Definition of safety ranges (BFI, CSM, DUNAFERR, AALTO) Certain cr itical p arameters wer e i nvestigated f rom BFI which wer e r elated t o d efects an d p roduct quality. As an example mould flux entrainment was one of the primary sources of surface and internal defects in continuous casted steel products [35]. The m ost c ommon m echanism f or t he e ntrainment o f l iquid f lux i n t he m ould o f a c ontinuous s lab caster was b y f luid f low n ear t he s teel melt/liquid f lux i nterface. The s teel melt f low came from t he SEN ports and was redirected by the narrow sides of the mould towards the interface. At the interface between the two fluids a wave developed. When near the interface the shear rate of the steel flow was great and a critical velocity was exceeded emulsification of liquid mould flux droplets occurred, like it was observed in the physical measurements. Such a critical velocity was computed from a force balance between the internal force of the steel melt stream and the buoyancy force of a mould flux droplet from Equation 5. A critical velocity of 0.39 m/s for the melt flow was computed. But it was observed from physical modelling that unsteady fluid flow phenomena led to a droplet entrainment occurred at lower flow velocities than the critical velocity at the interface [36,37]. Therefore, the safety ranges for the liquid flux thickness, turbulent kinetic energy, surface velocities and surface wave heights at the interface were evaluated as presented here from all the results obtained from exact s olution of p hysical la ws, o bservations in th e p hysical m odelling a nd th e r esults f rom th e numerical computations (Table 5-17).

Table 5-17. Critical parameters and safety ranges derived from the fluid flow investigations of BFI. [38,39]

Critical parameters Safety ranges

Minimum Liquid flux thickness 8 - 10 mm

Maximum Surface velocity 0.2 – 0.4 m/s

Maximum Surface wave height 15 – 20 mm

Two c ritical p arameters w ere d efined b y OBUDA for ch aracterising t he centreline s egregation: the porosity and relative flow rate of the mushy liquid. These two parameters depends on the chemistry of steel, on technological data of casting process and – very sharply – on the setting strategy and condition of supporting rolls. The LMI model takes into account these parameters and calculates porosity (Table 5-18) and on mushy liquid flow rate parameter (Table 5-19).

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Table 5-18. Critical parameter: porosity level in the centre part of slab. Critical parameter P [mm2], Porosity level in the centre part of slabs

Defects controlled porosity, centreline segregation, centreline discontinuity in the s lab and as a result discontinuity in the centreline of hot rolled strips and plates

Remark: centreline s egregation i s cau sed p artly b y p orosity an d p artly b y macrosegregation in the centre part of slab

Determination – calculation method

LMI (Liquid Motion Intensity) 2D model

Mathematical m odel for d etermination of shrinkage and pl astic de formation of solidifying shell taking into account the following parameters:

• Shrinkage of shell due to solidification and cooling • Nominal position supporting rolls (nominal tapering) • Real position of supporting rolls (measured by roll checker) • Misalignment of rolls • Eccentricity of rolls • Bulging of shell between rolls

Calculation t he v alue o f v olume ch anges d ue t o s hrinkage an d plastic deformation in that mushy area of the slab (mushy liquid/mushy ratio lower than 0.3), where the free flow of mushy liquid is highly retarded.

Safety range On t he basis o f t heoretical co nsiderations w hich ar e i n r elative g ood accordance with t he a vailable e xperiences co ncerning t he DUNAFERR casting machine

P =< 6: small risk of porosity, it can be eliminated by hot rolling

P > 6: high risk of porosity, generally cannot be eliminated by hot rolling

Remark: t he el imination o f cen treline po rosity hi ghly de pends o n t he thickness of rolled product

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Table 5-19. Critical parameter: Relative flow rate of mushy liquid in the centreline of slab. Critical parameter

F [mm/mm], Relative flow rate of mushy liquid at the liquid/mushy boundary in the centreline of slab

Defects controlled macrosegregation, centreline segregation, macrosegregated centreline area of slab and as a result centreline segregation in the hot rolled strips and plates (in

general higher carbon, manganese and sulphur content in the centre part than the nominal values)

Remark: centreline segregation is caused partly by porosity and partly by macrosegregation in the centre part of slab

Determination – calculation method

LMI (Liquid Motion Intensity) 2D model

Mathematical model f or d etermination of s hrinkage an d p lastic d eformation of solidifying shell taking into account the following parameters:

• Shrinkage of shell due to solidification and cooling • Nominal position supporting rolls (nominal tapering) • Real position of supporting rolls (measured by roll checker) • Misalignment of rolls • Eccentricity of rolls • Bulging of shell between rolls

Calculation the value of relative flow rate of mushy liquid in that mushy area of the s lab ( mushy l iquid/mushy r atio hi gher t han 0 .3), wh ere t he f ree f low o f mushy liquid is not retarded.

Safety range On the basis of theoretical considerations which are in relative good accordance with the available experiences concerning the DUNAFERR casting machine

0 < F < 0.001: small risk of centreline macrosegregation, the macrosegregated mushy liquid is a little bit squeezed out from the mushy area, the mushy liquid moves in the direction of the meniscus inside the slab.

F < 0: high risk of centreline macrosegregation, the macrosegregated mushy liquid is sucked into the mushy area, the mushy liquid moves in the direction of casting inside the slab.

F > 0.001: higher risk of centreline macrosegregation, the macrosegregated mushy liquid is drastically squeezed out from the mushy area.

Steel level variation in the mould DUFERCO has found the several reasons for melt variation in the mould at its billet caster. The effect of cutting the billets with shear could be seen as a perturbation in the surface level and investments on new oxygen-cutting finished those perturbations. The bender of the caster was changed to new system from one-point to three-point bending (from 6° to 12°to 21° to infinity). Also the old straightener of the caster was replaced with new and now the s traightening works without shaking the billet. Age of the sliding gate (numbers of casts) could have an impact on steel level variation in the mould. Figure 5-38 shows great melt level variation in sequences with different sliding gate age, 188 heats (on the left) and 151 heats (on the right).

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Sequence 16543 Sequence 16489 Age of the sliding gates : 188 heats Age of the sliding gates : 151 heats

Figure 5-38. Steel level variation in the mould and effect of age of sliding gate.

Indicators for critical steel grades: Copper equivalent and ferrite potential Up-setting tests were performed for cold-headed steel grade in order to determine the crack formation sensitivity with different casting parameters. The following casting parameters and conditions showed to have the influence on the crack formation: Mould tonnage (wear), control of copper equivalent and speed of casting are the first optimised parameters. (Figure 5-39).

Figure 5-39. Influence of operating parameters on up-setting tests for cold-headed steel grade.

SNiSnCuCueq %2%%10% ×−−×+= (8) Controlling the following features have shown to have a positive impact on the up-settings test results. The effect of these features and the results can be explained like in Table 5-20.

Table 5-20. Impact of 3 factors to the up-setting tests results.

Feature

Effect Result

Mold tons = Proper taper Fine grain in chill zone Premature wear of Ni thickness

No Cu pick-up at surface of billet Avoid craze cracking

Copper equivalent control Boundary fragilisation of austenite

Avoid hot shortness in hot rolling

Casting speed Control of os cillation ma rks depth

Avoid p ropagation of s urface defect

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The i nfluence o f t he ch emical composition o n d efect can b e s hown b y t he Ferrite p otential ( Fp): Manfred Wolf [40] developed a s imple b ut u seful te chnique to e stimate th e in itial solidification structure, wh ich plays a k ey r ole i n d etermining t he p otential f or cr acking o r s urface d efects i n cas t carbon and alloy steels. The approach involves the ferrite potential (Fp) of carbon and low-alloy steels, where Fp represents the proportion of δ-ferrite present during solidification. Fp is in turn defined by the “carbon eq uivalent” ( Cp), wh ich cl assifies t he al loying el ements p resent i n t he steel i nto t hose t hat stabilise either ferrite or austenite. The coefficients used in Wolf’s equation (Equation 8) are d erived f rom measurements o f p roduction steel s amples, an d co nsequently t he eq uations ar e s trictly s emi-empirical. T he t endency f or constitutionally related defects in continuous casting; such cracking, depressions and stickers are then plotted as a function of Fp. Such diagrams are useful for steel grades that are prone to casting problems, which do not occur in other grades of nominally similar chemistry or physical properties. The diagram can also be useful when casting new steel grades, in terms of indicators to help selecting taper, mould and secondary cooling parameters, mould powders etc. However, it must be remembered that the model is semi-empirical and the results are an indication not absolute values. Note that the diagram do not take into acco unt t he cooling r ate, w hich determines di ffusion r ates a nd t hus t he de viation f rom a n equilibrium structure for a specific steel composition. For carbon and low alloy steels:

( )pp CF −×= 5,05,2 (9a) Where v alues o f Fp>1 ar e i ndicative o f a f ully ferritic s tructure ab ove a nd below t he s olidus temperature. Pure δ iron has a value of 1.25 and other alloys with ferrite stabilisers such as Cr and Si have v alues h igher t han 1 ( e.g. s ilicon steels an d 4 30 s tainless g rades). Val ues < 0 indicate a f ully austenitic structure. (Figure 5-40) The carbon equivalent is calculated using Equation 9b

STiMoCrSiNNiMnCC p %7.0%24.0%1.0%04.0%14.0%7.0%1.0%04.0% −−−−−+++= (9b)

Figure 5-40. Ferrite potential tendency indices.

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Critical parameters and rules for Duferco steel grades 1.Critical Steel Grades: cold-headed steels (C-Mn-B-Ti)

• Casting speed is an important parameter playing a role in the quality of the billet, as well as for internal qua lity ( powder e ntrapment) a nd f or s urface qua lity. DUFERCO set up its c asting speed safety range up to 2 m/min.

• The s econdary c ooling i s o ne i mportant p arameter b ecause i t d efines t he t emperature d uring

bending which has to be over 1100°C. By using a menu of 0.32 l/kg in zone 0.30 l/kg in zone 1 and 0.20 l/kg in zone 2 DUFERCO increased the quality of the cold-headed steels.

• The mould powder is determinant to the heat transfer in the mould and its viscosity is of course

crucial, too. DUFERCO chose the Syntherm GB 1022/M from Intocast for this steel grade. • The mould itself need to be in good shape DUFERCO cast this steel grade only with a mould

with a lower age than 1000 tons. 2. Critical Steel Grade C10 (C-Mn-Ti peritectic steel)

• The critical parameters for this steel grade are the same as with the cold-headed grades above, except for the mould powder : Duferco uses a special powder for peritectic steel (Syntherm GB 535/P from Intocast)

3. Critical Steel Grade C72D2 (high carbon steel)

• The most critical parameter for this steel grade is the secondary cooling. It needs to be set-up to provide a mushy zone between 25-35% at the final stirring zone thus having lower segregation levels. To achieve this DUFERCO uses hard cooling 0.53 l/kg in zone 0, 1.2 l/kg in zone 1 and 0.28 l/kg in zone 2.

Quality indices from solidification model IDS and austenite decomposition model ADC (AALTO) In t erms o f d efining cr itical p arameters i n co ntinuous cas ting t he f ollowing s eries o f mathematical quality indices were determined b y AALTO for s teels with the data o f IDS s olidification mod el and austenite d ecomposition model. T hese i ndices describe i f p hase t ransformations an d precipitate formations occur in unfavourable time. Each quality index can get values between 0 and 1. Value QI=0 refers t o ex cellent s teel q uality wh ereas QI =1 refers t o v ery p oor s teel q uality. Qu ality i ndices ar e divided i nto 1) s olidification r elated i ndices and 2) a ustenite decomposition r elated in dices. T he required data are obtained from IDS and ADC models (local cooling rates from Tempsimu model and the d ynamic cas ting s imulator C astManager). As a r esult, qua lity i ndex v alues for di fferent pa rts of continuously cast strands are obtained. Based on simulations with IDS model four quality indices for high temperatures are created to describe the quality of the solidifying cast strand. Solidification related quality indices 1. Strengthening problem in mushy zone QISTR

During s olidification s trengthening o f steel s tarts a t T ZST, ze ro s trength t emperature, wh ere s olid fraction, f s is 0. 80. Strengthening w ill b e d isturbed if s teel has s tarted to s olidify as f errite a nd strengthening h as j ust s tarted an d t hen au stenite s tarts t o f orm b etween f errite an d l iquid cau sing shrinkage to steel structure. During austenite formation steel shrinks and cracks might be formed to the weak s teel s trand s tructure (hot cracking). Thus, the closer the austenite s tart temperature, TAUS+ is to TZST, t he more s trengthening w ill be di sturbed a nd r isk f or c racking i ncreases. Quality i ndex for strengthening problem in mushy zone QISTR

85

⋅

∆−−= 3.02 )()3(20.0exp1

dtdT

dTdf

TQISTR

γ

(10) where ∆T=abs(TZST-TAUS+) is a p ositive temperature difference between the zero s trength temperature (TZST) and austenite start temperature (TAUS+) (IDS output), dƒγ/dT is the growth of austenite fraction as a function of temperature (IDS output) and dT/dt is a cooling rate (°C/s). An schematic description of the change of index QISTR as the carbon content changes in low-alloyed steel is Figure 5-41. The index gets its maximum value as the TZST and TAUS+ curves intersect (∆T≈ 0, red circle). The index increases with i ncreasing c ooling rate a nd t hus di sturbing m ore t he s trengthening o f t he s olidifying s tructure. (IDS takes into account the effect of all the other elements, carbon the most effective).

Figure 5-41. Schematic presentation of quality index QISTR.

2. Ductility drop close to solidus temperature QISOL In the end of solidification, segregation of the most chemical elements increases (Figure 5-42a). With certain elements (for example phosphorous, sulphur and boron) segregation can be so strong that local solidification is considerably delayed. This decreases ductility of steel close to solidus temperature and exposes s trand t o h ot cr acking. Below T SOL ductility recovers a s th e in terdendritic s egregation “collapses”. The presence of austenite slows this event since the diffusion of elements is a lot slower in austenite than in ferrite. Decrease in ductility and thus worsening of cast quality is described here with index QISOL

+∆−−= 3.05.0 ))(31(05.0exp1

dtdTfTQISOL

γ (11)

where ∆T=T2%L-TSOL is the temperature difference in the end of solidification, when the liquid fraction drops from 2% to 0.5% (IDS output, fraction 0.5% equals to TSOL), ƒγ is the austenite fraction at solidus temperature (IDS output) and dT/dt is the cooling rate (°C/s) (Tempsimu and CastManager output). A schematic description of the change of index QISOL with changing carbon content in low-alloyed steel is in F igure 5-42b. The v alue o f i ndex QISOL increases as t he s olidification t ransforms t o b e m ore austenitic. As the cooling rate increases, the value of the index increases by weakening this “solidus-ductility” (Figure 5-42c).

86

(c)

Figure 5-42. a) Background of quality index QISOL. b) Graphical presentation of quality index QISOL and c) Effect of cooling on QISOL.

3. Disturbance of shell growth close to solidus temperature QISHE Heat transfer between a cast strand and a mould is uniform if solidification has completely been ferritic or austenitic. A thin shell which has grown like this is pressed tightly towards the mould by ensuring good and even heat transfer from strand to mould. Heat transfer is disturbed if austenite starts to form in a recently solidified ferritic shell (close to the solidus temperature). Then the shrinkage occurring during the ferrite to austenite phase transformation creates stress to the strand shell and it can be detached from the mould surface. Thus heat transfer weakens and shell growth is disturbed (Figure 5-43a). In the worst case this can lead in breakout of the cast strand shell. In the milder cases defects such as hot spots, longitudinal surface cracks and star cracks can be formed. Also hot tearing of structure might occur w hen t he s hell s urface i s de tached f rom t he m ould a nd he atens r apidly. T hen m icrostructure becomes co arser an d t he s trand i s ex posed t o t ransversal c orner cr acks at t he s traightening s tage. Surface d efects a re as sumed t o b e t he more p robable t he cl oser t he au stenite forms t o t he s olidus temperature and the stronger is the ability of austenite to grow in ferrite (red point in Figure 5-44b). The index QISHE gets its maximum value as TSOL ja TAUS+ curves intersect (Figure 5-44c) (∆T≈ 0, red circle). As cooling rate increases the values of the index grow thus disturbing more the shell growth.

(c)

Figure 5-43. a) Background of quality index QISHE b) Graphical presentation of quality index QISHE.and c) Effect of cooling on QISHE.

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Disturbance of shell growth and susceptibility to surface crack is described by quality index QISHE

⋅

∆−−= 3.02 )()3(5exp1

dtdT

dTdf

TQISHE

γ

(12)

where ∆T=abs(TSOL-TAUS+) is th e positive t emperature d ifference b etween t he s olidus t emperature (TSOL) and austenite formation temperature (TAUS+) (IDS-output), dƒγ/dT is the austenite phase growth in t erms o f t emperature ( IDS-output), d T/dt is th e lo cal c ooling rate (°C/s) of the s trand ( output o f TEMPSIMU and CastManager heat transfer models).

4. Ductility drop induced by large grain size QIGRA Large austenite grain size is known to decrease the ductility of steel. This problem is typical for low-alloyed s teels w ith h igh solidus temperature. T hen t he au stenite g rains h ave f avourable k inetic prerequisities to g row. During s traightening o f th e s trand a c oarse s tructure ( with lo w d uctility) c an expose the strand to transversal corner cracks. Ductility drop (and thus weakening of quality) because of large grain size is described with index

−−= 3)

3300(exp1

γDQIGRA (13)

where

)80

exp(1044.3)/exp(1

)/exp(1836.01841.0 9γ

γ TdtdT

dtdTD −⋅++

−= (14)

is the calculated grain size (µm) (IDS model). In Eq. (6) Tγ is the highest temperature (°C), where the structure can b e f ully austenitic ( Figure 5-44a) ( IDS output) a nd d T/dt i s th e c ooling r ate ( °C/s) (Tempsimu and CastManager output). Figure 5-44b schematically describes the change of index QIGRA with c hanging c arbon c ontent i n l ow-alloyed s teel. T he i ndex QIGRA gets i ts m aximum v alue as temperature T γ gets i ts h ighest possible value (red circle). As the cooling rate increases the grain s ize becomes smaller. Then the index values decreases and (which means “grain s ize –ductility” becomes better.

Figure 5-44. a) Background of quality index QIGRA. b) Graphical presentation of quality index QIGRA and effect of cooling on QIGRA.

(a) (b)

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Austenite decomposition related quality indices Based o n s imulations w ith a ustenite d ecomposition model ( ADC) th ree q uality in dices f or low temperatures have been created. These indices describe quality of low-alloyed steel for a specific phase transformation or precipitation incident. 5. Ductility drop induced by increased precipitation growth QICOM Inclusions f ormed d uring s olidification impair d uctility o f s teel i n a d endritic s cale. Ho wever, m ore dangerous t han i nclusions a re pr ecipitations ( compounds) w hich f orm i n g rain bo undaries i n l ow temperatures. P roviding t hat co oling of strand i s r emarkably s lown d own ( for e xample at s econdary cooling area in continuous casting) the growth of precipitations may accelerate. This naturally decreases ductility o f grain b oundaries. A nother factor w hich s timulates th e g rowth o f precipitations is th e austenite d ecomposition. On ce t he au stenite d ecomposition ha s s tarted, t he b oundary be tween t he growing phase and austenite moves (shifts) towards the grain centre the more effectively the bigger is undercooling a nd th e s maller is th e d ominating c ooling r ate after th is. D uring s olidification, a s th e phase interface moves to austenite areas, which were already passed, where the content of precipitations forming elements, such as, Al, Nb, Ti, V is still high. (Figure 5-45).

Figure 5-45. Background of quality index QICOM. Typical strongly growing precipitations are AlN, NbC, TiC and VC (nitrogen can be present also in the last th ree). Lowering o f d uctility c aused b y s trong p recipitation g rowth a nd i mpairing th e q uality represents QICOM index

[ ]∑∑ −−−= )(100exp1 1200C

CC

COM ffQI (15) Where ΣƒC is a sum of mole fraction of all the precipitations in temperature T and ΣƒC

1200C and is the corresponding mole f raction in 1200°C (both t erms a re calculated with IDS model us ing the cooling rate obtained from the heat transfer models, Tempsimu and CastManager). Figure 5-46 presents the change of index QICOM as a function of temperature in low-alloyed steel (blue curve). The value of index QICOM increases and ductility weakens as cooling slows down and austenite decomposes ( both o f t hem s timulate f ormation o f p recipitations.). As t he co oling r ate i ncreases t he value o f i ndex b ecomes s maller ( dotted l ine) an d t he s tructure b ecomes m ore ductile. Def ormation, instead, r aises t he i ndex v alue an d degrades d uctility. D eformation d oes n ot af fect t he f ormation o f compounds di rectly but i ndirectly b y s timulating austenite decomposition. In continuous casting it is essential how the index QICOM increases in the temperature range of straightening (yellow area in Figure

89

5-46). S teep g rowth i n t his “d eformation zo ne” p redicts d efects, s uch as , t ransversal c orner cr acks. Instead, milder growth (consequent on faster cooling) or moderate growth outside the area, decrease the probability of defects, instead.

Figure 5-46. Graphical presentation of quality indexes QICOM and QIADC.

6. Ductility drop in start of austenite decomposition QIADC Decomposition o f au stenite u sually s tarts f rom t he au stenite g rain b oundaries (Figure 5-47). In t he beginning of decomposition small amount of new phase (for example proeutectoid ferrite or cementite) lowers duc tility i n the grain boundaries, but a s t he amount o f n ew p hases i ncrease d uctility s tarts t o recover. An assumption is made here that ductility obtains the lowest value when 10% of austenite has decomposed. This corresponds to a thin film around a round austenite grain when the film thickness is 3.5% of the grain radius. A drop in ductility (and weakening in strand quality) is described with the index

[ ]ADCADC fQI 30exp1 −−= ƒADC<0.1 (16a)

[ ]3)/(003.0exp1 ADCADC fQI −−= ƒADC>0.1 (16b)

where ƒADC is a fraction of decomposed austenite in temperature T (is calculated with IDS model using the cooling rate calculated with heat t ransfer models Tempsimu and CastManager). Index QIADC gets values b etween 0 -1 a nd i ts g rowth i ndicates w eakening o f s trand qu ality in te rms o f a ustenite decomposition. E quation 16a d escribes weak ening o f d uctility wh en t he v alue o f p arameter ƒADC obtains values between 0-0.1 (0-10%), whereas Equation 8b describes recovering of ductility when the value of ƒADC grows between 0.1-1 (10-100%). Figure 37 pr esents t he change of i ndex QIADC as a f unction o f t emperature i n l ow-alloyed s teel ( red curve). The index value increases as the austenite decomposition proceeds from 0 to 10%. After this the index v alue s tarts to f all a nd d uctility b ecomes b etter. As 5 0% o f au stenite h as b een decomposed ductility i s al ready rather good. When cooling rate increases the index decreases (dotted l ine) and so ductility becomes better whereas deformation lifts the value of QIADC and drops ductility. In continuous casting it is important how the index QIADC grows in the frame of strand temperatures in the straightening area (yellow area in Figure 36, compare with the index QI COM). Steep growth in this “deformation zo ne” p redicts defects, such as , transversal corner cracks. Instead, m ilder growth

90

(consequent on faster cooling) or moderate growth outside the zone, decrease the probability of defects, instead.

Figure 5-47. Background of quality index QIADC.

7. Hard final structure QIHAR Final structure of low-alloyed steel can be estimated with the following Equation

MARBAIbaiFER HV)(HV)(HV)(HV marCpcpeap ffffffff +++++++= αγα (17) where terms ƒα, ƒγ, ƒpα and ƒpea represent fractions of soft ferritic phase fractions (α=ferrite, γ=austenite, pα=proeutectoid ferrite, pea=pearlite), terms ƒbai, ƒpc and ƒC represent fractions of medium hard phases in s tructure ( bai=bainite, p c=proeutectoid c ementite, C =precipitations) and t erm ƒmar describes a fraction of the hardness phase, martensite, in structure (Figure 5-48). The ar tificial cl assification of austenite i nto t he s oft p hases as wel l as p roeutectoid cem entite and precipitations i nto t he m edium ha rd p hases do es no t produce a bi g e rror a s t heir po rtions i n r oom temperature are small. All p hase f ractions i n Equation (9) can be cal culated wi th IDS m odel. British S teel C orporation h as presented the following equations to the terms HVFER, HVBAI and HVMAR HVFER = 42+223CC+53CSi+30CMn+7CCr+19CMo+12.6CNi+ (10-19CSi+8CCr+4CNi)⋅log(dT/dt) (18) HVBAI = -323+185CC+330CSi+153CMn+144CCr+191CMo+65CNi+ (89+53CC-55CSi-22CMn-20CCr-33CMo-10CNi)⋅log(dT/dt) (19) HVMAR = 127+949CC+27CSi+11CMn+16CCr+8CNi+21⋅log(dT/dt) (20) where C i is a wei ght percent [wt%] of a co mponent and dT/dt is an average predominant cooling rate during austenite decomposition [oC/hour] (TEMPSIMU-output). The equations (10)-(12) a re valid for the compositions up to 0.7wt%C, 0.6wt%Si, 1.6wt%Mn, 0.5wt%Mo and 9.9wt%Ni. If hardness is not a desired p roperty, f or ex ample b ecause of r eheating i nduced cr acking, can t he dr op i n ductility be represented as

1000/HVQIHAR = (21) where the total hardness is calculated with a Equation (17).

91

CAS F304L1 (heats 72142-143) CAS 420A7 (heats 72299-72300)

0

0.02

0.04

0.06

0.08

0.1

0 0.02 0.04 0.06 0.08 0.1

[m]

[m]

0

0.02

0.04

0.06

0.08

0.1

0 0.02 0.04 0.06 0.08 0.1

[m]

[m]

undeformed

def., z=0 (meniscus)

def., z=-(1/10)h

def., z=-(2/10)h

def., z=-(3/10)h

def., z=-(4/10)h

def., z=-(5/10)h

def., z=-(6/10)h

def., z=-(7/10)h

def., z=-(8/10)h

def., z=-(9/10)h

def., z=-h (mould bottom)

(h = mould height)CAS F304L1 (heats 72142-143) CAS 420A7 (heats 72299-72300)

0

0.02

0.04

0.06

0.08

0.1

0 0.02 0.04 0.06 0.08 0.1

[m]

[m]

0

0.02

0.04

0.06

0.08

0.1

0 0.02 0.04 0.06 0.08 0.1

[m]

[m]

undeformed

def., z=0 (meniscus)

def., z=-(1/10)h

def., z=-(2/10)h

def., z=-(3/10)h

def., z=-(4/10)h

def., z=-(5/10)h

def., z=-(6/10)h

def., z=-(7/10)h

def., z=-(8/10)h

def., z=-(9/10)h

def., z=-h (mould bottom)

(h = mould height)

Figure 5-48. Background of quality index QIHAR. Task 5.6 Execution of calculations with all the provided data and tuning of the safety ranges (BFI, CSM, DUNAFERR, AALTO) CSM has carried out 3D thermo-mechanical FEM simulations of the mould and 2D thermo-mechanical simulations of the both steels of CAS (F304L1and 420A7) to read the resulting fields from the point of view o f t he d etected d efect cl ass an d to find a p ossible r oute to m anage g host line f ormation w hile casting. MOULD - The top of the mould is usually constrained by a flange. Distorted profiles of inner surface of the mould’s cross-section have been graphed in Figure 5-49. The profiles are sliced at different levels from the meniscus. The mould body enlarges about 0.1 mm along all its body apart its free end, where the enlargement is its maximum and equals to about 0.2 mm in both the heats considered.

Figure 5-49. Distorted profiles of inner surface of the mould’s cross-section at different levels below the meniscus (deformation enlarged by a factor 100; e.g. deformation = (0.02/100)m = 0.0002m=0.2mm); a) heat

of steel CAS F304L1; b) heat of steel CAS 420A7.

STEEL - The surface temperature maps are shown in Figure 5-50. The corners are the coldest spots; at mould exit, the corner of steel grade 420A7 reaches 715°C while the corner of grade F304L1 reaches 850°C. The corresponding results in terms of steel displacement (Figure 5-51) consist of shrinkage of the steel CAS 420A7 (1.3 mm) higher than the one of steel CAS F304L1 (1.0 mm). The displacement map on the outer shell surface shows the highest shrinkage around the corner.

a b

92

These results must be interpreted taking into account also the thermal evolution of steel phases of both the considered steels (Figure 5-52). Solidification of the steel compositions in Table was calculated with IDS model [17-20] (by AALTO) (non-equilibrium s imulation). The r esults s howed t hat t he c omputed r esidual δ-ferrite fraction a t t he solidification temperature in s teel CAS F304L1 (Figure 5-52a) has been found about twice the one in steel CAS 420A7 at the corresponding temperature (Figure 5-52b). Consequently, the shrinkage at the solidification c ompletion ( i.e. associated t o t he δ-ferrite to a ustenite tr ansformation) in th e f ormer is lower than in the latter (Figure 5-52c).

Figure 5-50. Temperature maps on the outer shell surface, showing the presence of hotter off-corner regions; a) heat of steel CAS F304L1; b) heat of steel CAS 420A7.

Figure 5-51. Displacement maps on the outer shell surface, showing the highest shrinkage around the corners; a) heat of steel CAS F304L1; b) heat of steel CAS 420A7.

93

According to th e s imulations, th e s hell a t th e m ould e xit is detached al l ar ound t he p erimeter; t he maximum detachment is found at the corner and is approximately 0.8 mm. The detachment found at the mid-face i s de termined b y the s hell i nward be nding r esulting f rom t he a bsence o f t he ferrostatic pressure in the computations.

Figure 5-52. a) Liquid and solid delta-ferrite fraction dependence on temperature in steel CAS F304L1; b) the

same for steel CAS 420A7; c) linear thermal expansion coefficient comparison between the two steels. The displacement fields computed for the mould and the steel permit to determine the steel-to-mould- gap (Figure 5-53). The evolutions along the mould height of the heat flux, the surface temperature and the gap profiles between mid-face and corner are graphed in Figure 5-54.

0.E+00

2.E-05

4.E-05

6.E-05

8.E-05

1.E-04

1.E-04

1000 1100 1200 1300 1400 1500 1600temperature [°C]

[K-1]

F304L1

420A7

00.1

0.20.30.40.5

0.60.70.8

0.91

1000 1100 1200 1300 1400 1500 1600

ferrite fraction

420A7 liquid fraction

TZST

00.1

0.20.3

0.40.50.6

0.70.8

0.91

1000 1100 1200 1300 1400 1500 1600

liquid fraction

ferrite fraction

F304L1

TSOL

°C

°C

0.E+00

2.E-05

4.E-05

6.E-05

8.E-05

1.E-04

1.E-04

1000 1100 1200 1300 1400 1500 1600temperature [°C]

[K-1]

F304L1

420A7

00.1

0.20.30.40.5

0.60.70.8

0.91

1000 1100 1200 1300 1400 1500 1600

ferrite fraction

420A7 liquid fraction

00.1

0.20.30.40.5

0.60.70.8

0.91

1000 1100 1200 1300 1400 1500 1600

ferrite fraction

420A7 liquid fraction

TZST

00.1

0.20.3

0.40.50.6

0.70.8

0.91

1000 1100 1200 1300 1400 1500 1600

liquid fraction

ferrite fraction

F304L1

00.1

0.20.3

0.40.50.6

0.70.8

0.91

1000 1100 1200 1300 1400 1500 1600

liquid fraction

ferrite fraction

F304L1

TSOL

°C

°C

a c

b

94

Figure 5-53. Steel-to-mould gap maps – a) heat of steel CAS F304L1; b) heat of steel CAS 420A7.

Figure 5-54. Both the steels - Evolution along the mould height of the heat flux (a), the surface temperature (b) and the gap (c) profiles between mid-face and corner.

In both cases the formation of the hot spot near in the off-corner region is clearly shown.

The computed gap is coherent with the heat f lux evolution from the mid-face region to a d istance of 45mm from it. In this region, a lower heat flux correctly corresponds to a higher gap. That coherence is missed in the off-corner region (35 mm around the corner) where a l ower heat f lux corresponds to a lower gap. The explanation of this different behaviour could be ascribed to a different stratification of the solid slag layers due to the different thermo-physical properties of the lubricating powders used for casting CAS F304L1 and CAS 420A7. One of the thermo-physical properties that can affect the heat transfer is the basicity index, the higher the basicity index the lower the heat transfer (CAS F304L1 is cast with a powder having a higher basicity index than CAS 420A7). The modelling stage of the activities has involved also the implementation of a hot-tearing index (in the FEM co mmercial code b y a u ser s ubroutine) t o s tudy t he “ ghost lin e” d efect cl ass. The “ ghost lin e” defect c lass i s found only on CAS s teels 420A7 and 410 macro-etched b illet sections (Figures 5-55b and 5-55c, to be compared to Figure 5-55a representing a defect-free sample of a billet section of steel CAS F304L1).

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

spec

ific

heat

flux

[M

W /

m2 ]

z = -0.10m - F304L1 420A7

z = -0.30m - F304L1 420A7

z = -0.49m - F304L1 420A7

0.E+00

1.E-04

2.E-04

3.E-04

4.E-04

5.E-04

6.E-04

7.E-04

8.E-04

9.E-04

1.E-03

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

gap

[m]

z = -0.10m - F304L1 420A7

z = -0.30m - F304L1 420A7

z = -0.50m - F304L1 420A7

Bar-surface temperature profile at mould exit

900

950

1000

1050

1100

1150

1200

1250

1300

1350

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08distance from bar mid-face, along the cross section perim. [m]

surf

ace

tem

pera

ture

[°C

]

z = -0.14m - F304L1 420A7

z = -0.34m - F304L1 420A7

z = -0.47m - F304L1 420A7

mid-face corner mid-face corner mid-face corner

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

spec

ific

heat

flux

[M

W /

m2 ]

z = -0.10m - F304L1 420A7

z = -0.30m - F304L1 420A7

z = -0.49m - F304L1 420A7

0.E+00

1.E-04

2.E-04

3.E-04

4.E-04

5.E-04

6.E-04

7.E-04

8.E-04

9.E-04

1.E-03

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

distance from bar mid-face, along the cross section perim. [m]

gap

[m]

z = -0.10m - F304L1 420A7

z = -0.30m - F304L1 420A7

z = -0.50m - F304L1 420A7

Bar-surface temperature profile at mould exit

900

950

1000

1050

1100

1150

1200

1250

1300

1350

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08distance from bar mid-face, along the cross section perim. [m]

surf

ace

tem

pera

ture

[°C

]

z = -0.14m - F304L1 420A7

z = -0.34m - F304L1 420A7

z = -0.47m - F304L1 420A7

mid-face corner mid-face corner mid-face cornera b c

95

Figure 5-55. Macro etched billet sections. a) steel CAS F304L1, example of defect-free sample; b) and c) CAS steels 420A7 and 410, examples of ghost-line defect in the off-corner.

The i mplemented i ndex ha s be en de duced f rom a w ork of M onroe and Beckermann [41] where the porosity fraction in s olid s

pf due to th e a pplication o f m echanical s trains a t th e d endrite r oots is modelled:

Hot tearing index dtfsol

LI

T

T

zzyyxx

l

ssp ∫

++==

•••

εεερρ , (22)

where sρ and sρ are the solid and liquid density values respectively

•

ε is the strain rate tensor t is the time

Referring to Figure 5-56, it results that at the mould exit, the computed non-zero hot-tearing regions in steel CAS 420A7 are globally wider than in steel CAS F304L1. Some of them (continuous lines) have an experimental feedback while some other has not: the highest hot-tearing values are located along the connection of the two side dendritic fronts, where the hot-tearing is sensibly reduced.

Figure 5-56. Hot-tearing index field on the steel billet section at the mould exit.

96

BFI undertook numerical computations with the validated models for all the data provided over a wide range of casting parameters. Certain critical parameters of interest to be investigated were evaluated in Task 5.5. Namely these were the interface velocities, liquid flux thickness of the mould powder and the wave height at the meniscus. The influence of the process parameters such as immersion depth, mould powder t hickness an d cas ting s peed o n t he cr itical p arameters were i nvestigated wi th t he t hree dimensional, tu rbulent, tw o-phase n umerical m odel t o c ompute t he t hermal f luid f low of t he s teel melt/liquid flux system developed by BFI in Task 2.2. Exemplarily the development of the liquid flux thickness at the meniscus in dependence of the casting speed with a fixed immersion depth of the SEN of 120 mm and a mould powder thickness of 60 mm is shown in Figure 5-57. Melting and solidification of the mould powder was considered in the numerical model. From the temperature dependent data of the mould powder the l iquid f lux, s inter and powder layer we re d istinguished, see also Task 2. 2, Figure 2-5. In th e liq uid flux l ayer a velocity f low f ield developed t hat was d riven f rom t he melt f low an d a wa ve at t he i nterface b etween t he melt an d t he liquid flux develops. The results of the numerical computations showed that with an increase of the casting speed the liquid flux thickness increased too. This resulted from a higher heat flux transferred to the mould powder at higher c asting s peeds. A m inimum of t he l iquid f lux thickness o ccurred n ear t he S EN wi th a l ower casting speed. The wave height at the meniscus in dependency of the casting speed, with the same fixed parameters for immersion depth and mould powder thickness as in the example above, is shown in Figure 5-57. The wave h eight i ncreased wi th t he i ncrease o f t he cas ting s peed. In co mbination with t he r esulting velocities at t he i nterface en trainment of m ould p owder d roplets was m ore l ikely at cas ting s peeds above 0.7 m/min in combination with immersion depth lower than 120 mm.

a)

b)

c)

Figure 5-57. Numerically computed liquid flux thickness and wave heights at the meniscus of the mould with an immersion depth of 120 mm and a mould powder thickness of 60 mm for different casting speeds a) 0.5

m/min b) 0.7 m/min c) 0.9 m/min BFI also undertook numerical computations with the developed model from WP 3 for the computation of the temperature and velocity distribution along the complete strand. An example for the computed temperatures along the strand is shown in Figure 5-58.

97

a) view from outside b) view from centreline (inside the strand)

Figure 5-58. Three dimensional temperature distribution along the strand (for better representation

compressed in casting direction), a) view from outside, b) view from centreline. The temperature distribution along the centre line, corner, narrow and wide side is shown in Figure 5-59. The influence of the immersion depth of the SEN can be seen in the temperatures on the narrow side inside the mould but has nearly no influence on the temperatures at the end of the secondary cooling zone. The influence of the casting speed is high on the temperature distribution.

98

a) b)

0.5 m/min 0.7 m/min

0.9 m/min

c)

Figure 5-59. Temperatures at the centre, the corner, the narrow and the wide side of the slab for different

immersion depth of the SEN a) 80 mm, b) 120 mm, and c) 160 mm. Calculation of the casting trials at DUNAFERR

Altogether a number of 41 casting trials were performed in the last semester at DUNAFERR. The main reason of these trials was the control of centreline segregation in the centre area of the slabs. During the trials special attention was paid to the roll setting accuracy and – partly as a result of the tests – the roll setting concept has been changed. DUNAFERR has two vertical slab casters with two strands. During the last project year the roller settings concept was changed from “original” into “modified” one. The ”original” and the “modified” roller tapers differs mainly in the last solidification part of the strand (see Task 5.4). One of the main reasons for the trials was to estimate the effect of roll setting change on the inner quality of cast product. The results of trials were evaluated on the basis of modelling data.

A num ber of 22 s labs wer e i nvestigated al so b y m eans o f B aumann p rints an d macroetching. In 2 0 casting cases the calculated and qualitatively evaluated level of centreline segregation in the slab were in good accordance, contradictions were found between them only in 2 cases. The worse inner quality of this latter two slabs can be explained by sequence starting position of them.

Additional evaluation of the results showed very good inner quality in those cases where the liquid pool depth w as a round 1 0 m eters. In g eneral, s horter poo l de pth r esults i n s lightly w orse i nner qua lity indices, but longer pool depth causes drastic worsening in quality. This i s because of the greater roll pitch after 10 meters.

99

Simulation of CAS steels (AALTO) AALTO set up the billet caster of CAS in the TEMPSIMU model. Setting up the casters to Tempsimu is needed to be able to simulate later the process with the on-line casting simulator, CastManager (Task 4.1). Tempsimu m odel i s r equired no t only f or s teady-state s imulation, b ut a lso f or d ynamic c asting simulations as the geometry and technical issues of the caster are set up in Tempsimu. The six heats, two o f austenitic s tainless s teel F304L1 (Table 5 -21) and four o f martensitic s tainless steel 420A7 (5-22) were simulated and studied. The heats were chosen by CAS in terms of quality of the billet and rods and divided in good quality heats and bad quality heats (Table 5-23). The goal was to find differences in solidification and cooling of the steels to determine parameters which are critical in terms of quality.

Table 5-21. Compositions of the studied heats of steel grade F304L1.

Table5-22. Compositions of the studied heats of steel grade 420A7 of CAS.

Table 5-23. Quality determination of the heat CAS studied and simulated. Solidification calculations of casting trials at CAS (AALTO) The results of solidification calculations with IDS model o f the compositions of steel grades F304L1 and 420A7 are displayed in Tables 5-24 and 5-25 (explanation of symbols in Table A-10 in Appendix 1). In these tables phase transformations and events during solidification and cooling of s teels can be seen. Table 5-24 indicates formation of harmful compounds Nb(C,N), V (C,N) and AlN wi thin grade F304L1 between 900-1000°C. By controlling secondary cooling the formation of these elements can be decreased wh en s urface an d co rner t emperature d oes n ot f luctuate o r cool d own s lowly in th is temperature range.

wt% C S P Si Mn Cr Ni Mo Cu Al V Nb N72887 0.021 0.02 0.037 0.35 1.3 18.16 8.2 0.36 0.55 0.004 0.08 0.012 0.07872888 0.02 0.027 0.029 0.33 1.28 18.08 8.1 0.29 0.38 0.004 0.09 0.014 0.08

wt% C S P Si Mn Cr Ni Mo Cu Al Ti N73012 0.21 0.022 0.022 0.33 0.71 12.45 0.2 0.05 0.06 0.004 0.01 0.06773205 0.19 0.025 0.026 0.31 0.7 12.34 0.26 0.06 0.11 0.005 0.01 0.06473237 0.2 0.027 0.021 0.29 0.72 12.25 0.37 0.07 0.1 0.004 0.01 0.06673428 0.21 0.027 0.023 0.25 0.69 12.33 0.4 0.04 0.11 0.004 0.01 0.07

F304L1 420A7 Heat no. 72887 72888 73012 73205 73237 73428

Quality bad good quite bad

bad bad good

100

Table 5-24. Solidification calculations of the studied heats of steel grade F304L1 of CAS (IDS model).

T[C] 72887 T[C] 72888 1454 LIQ_fer+

1456 LIQ_fer+

1427 aus+

1427 aus+ 1426 euf+

1425 euf+

1422 zst

1424 zst 1390 com+[(MnCr)S]

1396 com+[(MnCr)S]

1381 SOL

1385 SOL 1381 com+[(MnFe)S]

1385 com+[(MnFe)S]

1246 euf-

1260 euf- 975 com+[(CN)Nb]

985 com+[(CN)Nb]

917 com+[(CN)V]

931 com+[(CN)V] 902 com+[AlN] 903 com+[AlN]

Table 5-25. Solidification calculations of the studied heats of steel grade 420A7 of CAS (IDS model).

Table 5-26 displays quality indices and phase fractions of the studied heats at 25°C. Quality indices do not show any increased risk for cracking of steel compositions themselves as 0 equals to good quality and 1to poor quality.

Table 5-26. Quality indexes and phase fractions at 25°C in the heats of CAS.

Steel grade F304L1 420A7 Heat

Quality index 72887 72888 73012 73159 73205 73237 73428 QIstr-index 0.01 0.08 0 0 0 0 0 QIsol-index 0.25 0.23 0.24 0.22 0.22 0.24 0.26 QIshe-index 0 0 0.01 0.01 0.01 0.01 0.01

Phase % Ferrite 2.8 2.9 - 0.3 0.3 - -

Austenite 97 97 5 3.7 3.8 4.7 5 Martensite - - 95 96 96 95 95 Compounds 0.1 0.1 0.1 0.1 0.1 0.1 0.1

T[C] CG_73012-1 T[C] CG_73159-1 T[C] CG_73205-1 T[C] CG_73237-1 T[C] CG_73428-11486 LIQ_fer+ 1488 LIQ_fer+ 1488 LIQ_fer+ 1487 LIQ_fer+ 1486 LIQ_fer+1468 com+[(CN)Ti] 1467 com+[(CN)Ti] 1469 com+[(CN)Ti] 1467 com+[(CN)Ti] 1467 com+[(CN)Ti]1431 zst 1436 zst 1437 zst 1433 zst 1430 zst1411 aus+ 1410 aus+ 1411 aus+ 1414 aus+ 1417 aus+1411 euf+ 1409 euf+ 1410 euf+ 1413 euf+ 1416 euf+1387 com+[(MnCr)S] 1389 com+[(MnCr)S] 1390 com+[(MnCr)S] 1393 com+[(MnCr)S] 1393 com+[(MnCr)S]1381 SOL 1382 SOL 1382 SOL 1384 SOL 1384 SOL1381 com+[(MnFe)S] 1382 com+[(MnFe)S] 1382 com+[(MnFe)S] 1384 com+[(MnFe)S] 1383 com+[(MnFe)S]1298 euf- 1306 euf- 1305 euf- 1305 euf- 1303 euf-954 com+[AlN] 965 com+[AlN] 969 com+[AlN] 1019 fer- 1097 fer-934 fer- 325 mar+ 322 mar+ 948 com+[AlN] 952 com+[AlN]297 mar+ 303 mar+ 298 mar+

101

As CAS indicated in Task 5.2, steel grade 420A7 have problems with subsurface cracks in billets and which result often to formation ghost lines in rods. It was observed that ghost lines have consisted of segregated compositions of chemical elements. Microsegregation of steel grades F304L1 and 420A7 are compared i n Figure 5-60 with a r elation o f segregated c omposition of t he element at s olidus temperature divided by its nominal composition. As it can be observed sulphur and niobium content in solidus temperature is over 20 t imes more than their nominal contents, phosphorus around 9 t imes in F304L and 6 t imes i n 420A 7. D iffusion n ormally s mooths th e c ompositions, b ut if th e e lements accumulate enough diffusion is not able to equalise the contents (macrosegregation). Microsegregation of elements can be considered as initial severity values for possible macrosegregation severity which is dependent on liquid flows, shrinkage and actual finishing of liquid supply in final solidification. When comparing t he d ifference i n m icrosegregations i n F igure 5 -60 i t ha s t o be noticed t hat s teel g rade F304L1 di d no t c ontain a ny t itanium a nd w hereas s teel g rade 420A7 did no t h ave a ny ni obium no r vanadium.

Figure 5-60. Microsegregation of chemical elements in F304L1 and 420A7 steel grades. Heat transfer calculations of casting trials at CAS (AALTO) Heat transfer simulations have been performed for all the heats of both the steel grades of CAS studied in this project F304L1 and 420A7 with Tempsimu model (thermophysical material data from IDS as a function of temperature). The steady-state casting simulations show that there are only small differences in the results between the normal casting processes of the steel grades. (Figures 5-61 and 5-62) Mushy zone of the 420A7 is a b it larger and midface temperatures are around 50°C and corner temperatures around 20° C hi gher i n t he s econdary c ooling zones t han i n t he c ase o f F304L1 (secondary c ooling waters and casting speeds in Tables 5-2 and 5-3).

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Cr Ni Mn Mo Si Nb Ti Cu V Al P C N S

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F304L1

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Nb=25 F304L1S=25 420A7S=22 F304L1

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Figure 5-61. Midface and corner temperatures of steel grades F304L1 (heat 72888) and 420A7 (heat 73428) at CAS.

Figure 5-62. Liquidus and solidus temperatures of steel grades F304L1 (heat 72888) and 420A7 (heat 73428) at CAS.

Of all the heats of martensitic steel grade 420A7 cast at of CAS the heat 73428 was determined to have the be st q uality a nd t he heat 732 37 t o ha ve t he w orst qua lity. In t he s teady-state h eat t ransfer simulations practically no differences can be observed in the strand temperatures (Figures 5-63 and 5-64). The strand temperatures in the other two heats (73012 and 73205) were practically the same as in these first two heats mentioned above. According to the metallographic inspections the distance of the subsurface cracks from the billet surface was on average 14-15 mm. The crack formation location at the caster can be estimated from the crack distance from the surface and heat transfer calculation. The first area of low ductility in steels is right after solidus temperature (fraction of solid 1.0), between the zero ductility temperature ZDT (fraction of solid 0.99) and the zero strength temperature ZST (fraction of solid 0.80) [41]. When a nalysing t he s trand t emperatures i n F igure 5-63, t here i s h ard co oling at t he s ame l ocation. Midface t emperature fluctuates b etween 9 50°C an d 1 200°C v ery frequently an d co rner t emperature drops fast down to 800°C and rises up to 1000°C in a short distance. It seems rather possible that these rapid t emperature variations induce thermal s tresses to the cas t b illet and have most p robably caused

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X-midface 420A7 73428Corner 420A7 73428X-midface F304L1 72888Corner F304L1 72888

CornerMidface

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Tsol F304L1 72888Tliq F304L1 72888Tsol 420A7 73428Tliq 420A7 73428

103

these off-corner cracks s ince shell is 14-15 mm thick at around 1 m eter from meniscus (Figure 5 -64) and these dramatic temperature fluctuations occur very much in the same place (Figure 5-63). Thus, the rapid high amplitude temperature fluctuations are critical for the quality and it seems that water amount in the 1 st and 2 nd secondary cooling zones should be decreased (cooling water amounts in Tables 5-2 and 5-3). SEM investigations of F304L1 (Task 5.3) made by CSM revealed mould powder to be present in the cracks indicating that cracks have been formed in the mould. The simulations of CSM have focused on lubrication and thermo-mechanical behaviour of steel and mould in WP3 and WP5. Those calculations are actually more appropriate to describe the defect evidenced by SEM for this F304L1 steel grade than heat t ransfer s imulations made h ere. (Solidification c alculations w ith IDS m odel anyhow b rings information on solidification, phases and precipitations (Tables 5-24 and 5-25)).

Figure 5-63. Midface and corner temperatures in heats 73237 and 73428 of CAS (0-7m).

Figure 5-64. Liquidus and solidus isotherms in heats 73237 and 73428 of CAS. According to th e s olidification s imulations w ith I DS m odel it c an b e s een that h armful A lN is precipitated in temperature range 950-970°C with the studied steel compositions of 420A7 grade. Thus

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X-midface GOOD 73428Corner GOOD 73428X-midface BAD 73237Corner BAD 73237

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long time or fluctuations in these temperatures should be avoided in billet surface and especially in the corners which are sensitive for cracking during straightening . Dynamic heat transfer calculations of casting trial of CAS (AALTO) Figure 5-65 presents four c lips of from the beginning of casting to the s teady-state cas ting s imulated with d ynamic cas ting s imulator C astManager ( heat 7 3428, s teel g rade 4 20A7 o f C AS). On t he l eft picture o f t he cl ip i s s urface t emperature an d t he m iddle p icture i llustrates liquidus a nd s olidus isotherms in the centre plane of the billet (user interface draws at the moment only slab size relations). As the cast proceeds the liquid pool length increases (from the clip1 to clip 4 in Figure 5-65) until the more or less steady state casting condition is reached (clip4). On the right in the user interface are secondary cooling water flow rates for each zone. The influence of liquid pool length on surface temperature can be seen clearly in the clip 4. When liquid melt is present in a s trand it heatens up the surface temperature, but when a s trand is completely solidified the surface temperature decreases faster. On the utmost r ight the momentary casting parameters: date, heat, t ime, casting speed, crater end (=liquid pool) etc. and calculated values: liquidus and solidus isotherms in the cast s trand ( picture al so i n t he m iddle o f t he u ser i nterface, as m entioned), m easured an d cal culated mould heat transfer.

Clip 1 Clip 2

Clip 3 Clip 4

Figure 5-65. Dynamic simulations of heat 73428 of steel grade 420A7 of CAS with casting simulator CastManager.

105

Because o f t he h igh car bon co ntent 0 .2% i n m artensitic s teel 4 20A7, detrimental complex ca rbides M23C6 and M7C3 can be formed and caused cracking of the billets. (IDS model is not able to calculate these complex carbides.) Simulation of DUFERCO steels (AALTO)

AALTO simulated th e c old-headed steel g rades 20MnB4 a nd 30M nB4 o f DUFERCO. S teel g rade 20MnB4 was divided in two groups according to the mould powder used, Melubir 3011 and Syntherm GB 1022/M. In Task 5.2, Tables 5-8 and 5-9 DUFERCO has displayed casting parameter and quality data of the heats of steel grades 20MnB4 and 30MnB4. Tables 5-27, 5-28 and 5-29 show the simulated heats an d t heir compositions. These t wo h eats p er g roup were s elected b y DUFERCO from t he cast heats from Table 5-8 and 5-9 according to the quality of the wire rods. Thus, in the following three steel grade groups the one was determined as good quality heat and the other bad quality heat (Table 5-30). The ai m of t he s imulations was t o s earch for d ifferences i n t he h eats an d to find cr itical p arameters affecting the quality.

Table 5-27. Compositions of the studied heats of steel grade 20MnB4 with mould powder Melubir 3011 of DUFERCO. Heat 54795 good quality heat, 54797 bad quality heat.

Table 5-28. Compositions of the studied heats of steel grade 20MnB4 with mould powder Syntherm GB 1022/M

of DUFERCO. Heat 56319 good quality heat, 56317 bad quality heat.

Table 5-29. Compositions of the studied heats of steel grade 30MnB4 of DUFERCO. Heat 56708 good quality

heat, 56462 bad quality heat.

Table 5-30. Simulated heats of DUFERCO by AALTO.

Heat Steel grade Mould powder

Rolled [tons]

Rejected wire rods [%]

Quality

54795 20MnB4 Melubir 65.5 3.05% Good 54797 20MnB4 Melubir 96.0 14.4% Bad 56317 20MnB4 Syntherm 86.0 14.4% Bad 56319 20MnB4 Syntherm 88.0 0 % Good 56462 30MnB4 Syntherm 92.0 11.9% Bad 56708 30MnB4 Syntherm 66.0 5% Good

Heat no C% Mn% S% P% Si% Cu% Al% Ca% Ni% Cr% Mo% Nb% N2% V% B% Ti%54795 0.210 1.042 0.003 0.012 0.231 0.057 0.034 0.0014 0.038 0.054 0.008 0.002 0.0086 0.004 0.0035 0.03154797 0.207 1.057 0.002 0.014 0.245 0.053 0.037 0.0018 0.040 0.064 0.008 0.002 0.0089 0.004 0.0034 0.034

Heat no C% Mn% S% P% Si% Cu% Al% Ca% Ni% Cr% Mo% Nb% N2% V% B% Ti%56317 0.190 1.051 0.002 0.015 0.249 0.088 0.035 0.0018 0.046 0.069 0.011 0.001 0.0097 0.004 0.0037 0.03056319 0.201 1.079 0.001 0.013 0.205 0.086 0.033 0.0018 0.050 0.060 0.013 0.001 0.0104 0.004 0.0037 0.028

Heat no C% Mn% S% P% Si% Cu% Al% Ca% Ni% Cr% Mo% Nb% N2% V% B% Ti%56317 0.190 1.051 0.002 0.015 0.249 0.088 0.035 0.0018 0.046 0.069 0.011 0.001 0.0097 0.004 0.0037 0.03056319 0.201 1.079 0.001 0.013 0.205 0.086 0.033 0.0018 0.050 0.060 0.013 0.001 0.0104 0.004 0.0037 0.028

106

Solidification calculations of casting trials at DUFERCO (AALTO) The results of solidification calculations with IDS model of the compositions of steel grades 20MnB4 adn 30MnB4 are displayed in Tables 5-31 and 5-32 (explanation of symbols in Table A-10 in Appendix 1). In these tables phase transformations and events during solidification and cooling of steels can be seen. With steel grade 20MnB4 (Table 5-31) harmful compounds AlN and Nb(C,N) are formed around 1000°C and V(C,N) about in 750°C. By controlling secondary cooling the formation of these elements can be decreased when surface and corner temperature does not f luctuate or cool down slowly in this temperature range.

Table 5-31. Solidification calculations of the studied heats of steel grade 20MnB4 (IDS model).

Table 5-32. Solidification calculations of the studied heats of steel grade 30MnB4 (IDS model).

Quality index QIsol, approximately 0.65, indicates rather high cracking risk for both steel grades (Table 5-33). QISOL describes a d ecrease i n ductility a nd th us worsening o f cast q uality. In t he e nd o f solidification, s egregation o f t he m ost ch emical el ements i ncreases ( Figure 5-42a). With c ertain elements ( for e xample pho sphorous, s ulphur a nd bo ron) s egregation c an be s o s trong t hat l ocal solidification is considerably delayed. This decreases ductility of steel close to solidus temperature and

Heat 54795-1 Heat 54797-1 Heat 56317-1 Heat 56319-1Temperature [C] Event Temperature [C] Event Temperature [C] Event Temperature [C] Event

1600 com+[CaS] 1600 com+[CaS] 1600 com+[CaS] 1600 com+[CaS]1512 LIQ_fer+ 1512 LIQ_fer+ 1513 LIQ_fer+ 1512 LIQ_fer+1494 com+[(CN)Ti] 1496 com+[(CN)Ti] 1497 com+[(CN)Ti] 1496 com+[(CN)Ti]1484 aus+ 1484 aus+ 1483 aus+ 1484 aus+1481 zst 1481 zst 1481 zst 1482 zst1478 fer- 1476 fer- 1474 fer- 1478 fer-1418 SOL 1420 SOL 1421 SOL 1421 SOL1347 com+[(MnFe)S] 1244 com+[(MnFe)S] 1271 com+[BN] 1303 com+[BN]1222 com+[BN] 1200 com+[BN] 1243 com+[(MnFe)S] 1050 com+[AlN]1018 com+[AlN] 1022 com+[AlN] 1039 com+[AlN] 947 com+[(CN)Nb]1002 com+[(CN)Nb] 1000 com+[(CN)Nb] 942 com+[(CN)Nb] 805 Ae3976 com+[(FeCr)2B] 996 com+[(FeCr)2B] 904 com+[(FeCr)2B] 768 com+[FeMo2B2]807 Ae3 808 Ae3 812 Ae3 751 com+[(MnFe)S]741 com+[FeMo2B2] 740 com+[FeMo2B2] 766 com+[FeMo2B2] 743 com+[(CN)V]737 com+[(CN)V] 737 com+[(CN)V] 739 prf+ 728 prf+734 prf+ 732 prf+ 639 pea+ 689 com+[Ti2CS]639 pea+ 637 pea+ 635 com+[TiB2] 636 pea+639 com+[Ti2CS] 637 com+[Ti2CS] 598 pea- 618 com+[TiB2]635 com+[TiB2] 633 com+[TiB2] 589 pea-597 pea- 596 pea-

Heat 56462-1 Heat 56708-1Temperature [C] Event Temperature [C] Event

1600 com+[CaS] 1600 com+[CaS]1506 LIQ_fer+ 1506 LIQ_fer+1488 aus+ 1499 com+[(CN)Ti]1487 com+[(CN)Ti] 1489 aus+1486 fer- 1486 fer-1472 zst 1474 zst1401 SOL 1430 com+[Ti2CS]1260 com+[BN] 1410 SOL1208 com+[(MnFe)S] 1272 com+[(MnFe)S]1018 com+[(FeCr)2B] 1093 com+[(FeCr)2B]982 com+[(CN)Nb] 975 com+[(CN)Nb]861 com+[AlN] 948 com+[AlN]785 Ae3 784 Ae3761 com+[(CN)V] 752 com+[FeMo2B2]730 com+[FeMo2B2] 749 com+[(CN)V]706 prf+ 708 prf+649 pea+ 651 pea+601 pea- 606 com+[TiB2]

600 pea-

107

exposes s trand t o h ot cr acking. Below T SOL ductility recovers a s th e in terdendritic s egregation “collapses”. The presence of austenite slows this event since the diffusion of elements is a lot slower in austenite than in ferrite. (Task 5.5)

Table 5-33. Quality indexes and phase fractions at 25°C in the heats of DUFERCO.

Steel grade 20MnB4 30MnB4 Heat

Quality index 54795 54797 56317 56319 56462 56708 QIstr-index 0.12 0.13 0.24 0.16 0.00 0.01 QIsol-index 0.67 0.66 0.67 0.67 0.68 0.65 QIgra-index 0.26 0.28 0.28 0.28 0.17 0.21

Phase % Proeut. ferrite 9 8.8 10 8.6 3.8 3.5

Pearlite 90.9 91.1 89.9 91.3 96.1 96.4 Compounds 0.1 0.1 0.1 0.1 0.1 0.2

Heat transfer calculations of casting trials at DUFERCO (AALTO) Heat transfer calculations showed that heats 54795 and 54797 of grade 20MnB4 (Melubir) between 3-7 meters from meniscus the corner temperatures had maximum of 60°C temperature difference (Figure 5-66 and 5-67). Anyhow, those temperatures between 900-1000°C can be critical for the formation of the precipitations mentioned above and a risk for defects increases.

Figure 5-66. Midface and corner temperatures of heats 54795 and 54797 (0-20m).

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Figure 5-67. Midface and corner temperatures of heats 54795 and 54797 (0-7m).

The he ats o f s teel g rade 20M nB4 c ast with S yntherm mould po wder did n ot have an y ch anges i n surface t emperatures ( Figure 5 -68). With s teel g rade 3 0MnB4 t emperatures wer e al so o therwise t he same, but with the bad quality heat corner temperature reached rapidly 850 °C after the mould, which was about 70°C lower temperature than with the good quality heat (Figure 5-69).

Figure 5-68. Midface and corner temperatures of heats 56319 and 56317 (0-20m).

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Figure 5-69. Midface and corner temperatures of heats 56462 and 56708 (0-7m).

Effect of casting speed and secondary cooling The ef fect o f cas ting s peed an d s econdary cooling o n s olidification an d s urface t emperatures was studied. For the high casting speed case heat no. 54797 with a casting speed of 2.20 m/min was chosen. It was compared to heat 56317 with a casting speed of 1.85 m/min. (These casts had different mould powder (Table X, but the effect of the powder is not taken into account in these the simulations when comparing only casting parameters).

Table 5-34. Casting speed and secondary cooling of the heats 54797 and 56317.

As it can be observed from Figures X and Y that the increase of casting speed, increased the liquid pool with 1.7 meters.

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Casting speed [m/min]

Water flow rate Zone 1

Water flow rate Zone 2

Water flow rate Zone 3

Heat 54797 2.20 1.7 1.7 1.2

Heat 56317 1.85 1.5 1.5 1.1

110

Figure 5-70. Liquidus and solidus isotherms of heats 54797 (casting speed 2.20 m/min, secondary cooling water: zone1: 1.7 m3/h, zone2: 1.7m3/h, zone3: 1.2m3/h) and 56317 (casting speed 1.85 m/min, secondary

cooling water: zone1: 1.5 m3/h, zone2: 1.5m3/h, zone3: 1.1 m3/h).

Figure 5-71. Midface and corner temperatures of heats 54797 (casting speed 2.20 m/min, secondary cooling water: zone1: 1.7 m3/h, zone2: 1.7m3/h, zone3: 1.2m3/h) and 56317 (casting speed 1.85 m/min, secondary

cooling water: zone1: 1.5 m3/h, zone2: 1.5m3/h, zone3: 1.1 m3/h).

Dynamic heat transfer calculations of casting trial of DUFERCO (AALTO) Figure i llustrates m omentary clips f rom t he d ynamic h eat t ransfer c alculation C astManager o n-line simulator of t he pr evious c ase, he ats 5479 7 a nd 56317. On t he l eft p icture o f t he cl ip i s s urface temperature and the middle picture illustrates liquidus and solidus isotherms in the centre plane of the billet (user interface d raws at the moment only s lab s ize relations). Descriptions of u ser interface are given in Task 4.1. The influence of secondary cooling on surface temperatures can be observed. Also it can be seen how the liquid pool heatens up to the surface and how surface temperatures decreases after liquid pool end.

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111

Figure 5-72. Dynamic simulations of heat 54797of steel grade 20MnB4 of DUFERCO with casting

simulator CastManager (casting speed 2.20 m/min, secondary cooling water: zone1: 1.7 m3/h, zone2:

1.7m3/h, zone3: 1.2m3/h)

Figure 5-73. Dynamic simulations of heat 56317 of steel grade 20MnB4 of DUFERCO with casting

simulator CastManager (casting speed 1.85 m/min, secondary cooling water: zone1: 1.5 m3/h, zone2:

1.5m3/h, zone3: 1.1 m3/h)

2.3.6 WP6 DEVELOPMENT AND APPLICATION OF THE EMPIRIC ON-LINE MODEL OPTIMISED FOR PROCESS CONTROL Objectives in this Work Package was to find out empirical relationships between critical parameters and safety ranges as obtained from the casting trials and developed models in order to use them in the on-line casting simulator. As a consequence, the objective is to elaborate the guidelines for the extension of the new on-line model for detecting and controlling the casting process in other continuous casters. Task 6.1 Formulation of empirical relationships between the critical variables and input sets of input parameters (all partners) BFI assessed i nformation o n t he i nterrelation o f t he cr itical p arameters an d t he r elevant cas ting parameters. The cr itical p arameters wer e ap pointed f rom t he r esults o f t he n umerical c omputations undertaken in task 5.6. From this information, correlations could be derived, which in combination with the s afety r anges, s hould be us ed i n the LMI on-line m odel f rom OBUDA and DUNAFERR to evaluate situations were casting conditions will deliver good quality products. In general, these kinds of safety ranges could be used also in the CastManager on-line model by AALTO, as initial limits of the critical parameters calculated before the casting. Three examples are given for the development of the computed liquid flux thickness, wave height and the velocity at t he s teel melt/liquid f lux interface in dependence of t he casting speed. I t i s shown in Figure 6-1 that wi th an i ncrease o f t he cas ting s peed t he l iquid f lux t hickness i ncreases wi th f ixed thermal boundary conditions of the flux powder thickness and the heat transfer. A correlation between the liquid flux thickness and the casting speed, for an immersion depth of the SEN1 of 120 mm and a mould p owder t hickness o f 6 0 m m, wa s ex pressed ex emplarily o n t he r ight s ide o f t he d iagram i n Figure 6-1. The liquid flux thickness for all investigated parameters is shown on the left side of Figure 6-1, showing critical liquid flux thicknesses marked red, where the liquid flux thickness is lower than the critical value of 8-10 mm found from literature.

112

Figure 6-1. Numerically computed liquid flux thickness (minimum) for different casting speeds. The interrelation between the wave heights at the steel melt/liquid flux interface, shown in Figure 6-2, increased with the increase of the casting speed. The mathematical formulation for the correlation for an immersion depth of the SEN1 of 120 m m and a mould powder thickness of 60 m m was given in the equation on the right side of the diagram. The critical wave height of more than 15-20 mm found from the flow visualisations was marked red in the Figure.

Figure 6-2. Numerically computed wave height (maximum) for different casting speeds. The interrelation between the velocities at the interface of the steel melt/liquid flux, shown in Figure 6-3 increased wi th t he increase o f t he cas ting s peed an d t he decrease o f t he i mmersion d epth. T he mathematical formulation f or t he correlation for an immersion depth of t he SEN1 of 120 m m and a mould powder thickness of 60 mm was given on the right side of the diagram. The computed critical velocity of 0.39 m/s is not reached for the investigated parameters. Interrelations for the critical variables were evaluated for all the provided process data, under variation of the casting speed, immersion depth and mould powder thickness.

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Figure 6-3. Numerically computed velocity at the steel melt/liquid flux interface (maximum) for different casting speeds.

Inverse heat flux difference model (CSM) On the basis of the mechanism leading to the application of tensile stresses on the solidification front, (WP3), t he em pirical r elationship b etween t he cr itical variable i dentified i n t he h eat f lux d ifference between the midface and the corner and the process parameters can assume the following expression:

nC

mT

vCQ SOL

α=∆

(23)

where

SOLTα is the value of the linear thermal expansion coefficient at the solidus temperature

Cv is the casting speed

C , m and n are c oefficients t hat m ust b e ad justed wi th ex perimental m easures o f Q∆ on heats of different steels cast at different speeds

This expression states that the greater is the shell shrinkage, the greater is the expected detachment of the shell near the corner, resulting in a h igher Q∆ value. On the other s ide, h igher values of casting speed produce lower shell shrinkage and consequently reduced Q∆ values. That relation has later been updated taking into account that a casting powder with lower basicity index BI induces higher heat conduction:

( )( ) ( )nm

c

kT

BIvgapQ sol

α∝∝∆

(24) where k, m and n are coefficients.

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In these terms, a possible route towards a process regularisation (i.e. a gap regularisation) could involve the updating of the casting speed, the casting powder and the mould taper.

DUNAFERR and OBUDA has investigated cen treline s egregation an d n oticed t hat i n the case o f centreline s egregation t he c onnection b etween t he cr itical variables an d i nput parameters can not b e easily ch aracterised b ecause o f i ts co mplex p henomena. T he c ritical p arameters ( porosity level an d relative f low rate o f mushy l iquid) depends on al l of cas ting parameters, i e. chemical composition of steel, casting technology (superheat, casting speed, primary and secondary cooling intensities, etc.) and the setting and condition of supporting rolls must be taken into account. Special database was designed and prepared which consist of pre-calculated data of 22 casting cases. These casting cases contains both steady-state an d n on s teady-state t ime periods, s o t he effect o f cas ting p arameters on the v alue of critical p arameters can b e i nvestigated under non s teady-state c asting c onditions to o. T he d atabase contains the following calculation results:

• Complete t emperature d istribution i n t he s ymmetry p lane o f s lab ( for each t ime s tep i n steady and non-steady casting periods of the selected casting case)

• LMI calculation results for different roll setting concepts (in general four different cases of roll gap distributions were pre-calculated)

• LMI cal culation r esults f or t he ab ove mentioned cas es (2) b ut al so t he eccen tricities o f individual rolls were taken into account

• LMI calculation results for the above cases (2 and 3) with bulging

Casting cas e an alyser s oftware was d eveloped f or s tudying an d d isplaying t he cal culation r esults collected in the database.

Figure 6-4– as an example for the usage of the analyser software and database – shows the input data of the model and the calculation results of critical parameters. The on-line measured functions of casting speed and secondary cooling water amounts are given in diagram a), the model representation of these on-line measured parameters can be seen in graph b) for casting case no.1. The casting rate is constant for a g iven period of t ime (steady-state casting), but there i s a n egative peak in cas ting rate function representing a real transient in the casting process.

The c) diagram of the Figure 6-4 displays the half roll-gap distribution along the caster (black – without bulging, red – with bulging), t he solid s hell t hickness values (both f or l iquidus and solidus) and the shape of liquid pool, the relative flow rate of the liquid in the mushy, and finally the developed porosity level in the slab centreline. The d) part of the Figure 6-4 describe the instability of porosity and relative flow rate in the centreline as a function of time, caused by the summarised effect of individual rolls’ eccentricities. This latter diagram contains also the casting speed in order to study the effect of transient changes in casting speed on the porosity and flow rate functions.

The casting case analyser software is able to display the critical variables, flow rate of the liquid in the mushy and porosity level (graph c)) in each time step of the whole casting process (given in graph a)).

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a) b)

c) d) Figure 6-4. Input and output data of the Casting case analyser software (case no. 1)

A more c omplicated in dustrial c asting c ase is s hown in Figure 6-5. T he cas ting r ate f luctuates v ery heavily (graph a)) because of some clogging problems and as a result the porosity level is increasing continuously.

Representation of casting rate and pool positions

Representation of cooling

PorosityFlow rateSolid shellHalf gap

Casting rate and pool positions

Flow rate with eccentricities of rolls

Porosity with eccentricities of rolls

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a) b)

c) d)

Figure 6-5. Input and output data of the casting case analyser software (case No. 20).

The use of developed database and software gives the possibility to perform individual analysis of each casting case. The expected porosity level and the severity of the relative mushy liquid flow level can be predicted. Task 6.2 Estimation of the limits for the variable changes inside which a regular casting process is guaranteed (all partners) From t he BFI investigations it w as found f or a continuous s lab c aster th at th e liq uid f lux th ickness (Figure 5-57) and the wave he ight ( Figure 6-2) in combination w ith th e p reliminary e stimated s afety ranges were both parameters that can cause problems concerning the quality of the casted products. But within the investigated range of parameters there were also other critical variables, like the velocity at the steel melt/liquid flux interface and the turbulence, influencing the product quality as well. The p hysical modelling al ready gave a co mprehensive o verview o n t he m ould f low b ehaviour an d detailed information on critical operational states. Tendencies were elaborated from the measurements when i t was m ore l ikely t hat cas ting d efects m ay o ccur i n t he casting p rocess. T he n umerical computations o f th e s teel melt/liquid f lux f low gave more in formation on th e “ real” f low c onditions inside the s teel melt f low. The n umerical model p redicted cr itical p arameters l ike t he velocity at t he interface, th e liq uid flux t hicknesses o r t he wav e h eight, wh ich wer e n ot d irectly m easured o n-line during casting and linked them to process parameters which were measured on-line and thus available.

Representation of castign rate and pool positions

Representation of cooling

PorosityFlow rateSolid shellHalf gap

Casting rate and pool positions

Flow rate with eccentricities of rolls

Porosity with eccentricities of rolls

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Therefore “hidden” critical parameters (velocity at the interface and liquid flux thickness) were linked to monitored input parameters like immersion depth of the SEN and casting speed. Liquid f lux e ntrainment w as d efinitely observed in th e p hysical m odelling w hen th e v elocity at th e interface reaches a cr itical value computed from equation 4. When the critical value computed for the steel m elt/mould p owder i s reached, al so a s afety d istance t o t his v alue i s recommended d ue t o t he turbulent structure of the melt flow. The critical velocity was avoided when

• Immersion depth of the SEN was high (here more than 100 mm). • Casting speed was lower (here less than 0.7 m/min). • Port exit angle of the SEN was directed away from the interface steel melt/liquid flux.

Liquid f lux thickness was h igher when the s teel melt f low was d irected awa y from the interface, but liquid flux thickness was propagated when the steel melt flow was directed towards the interface. In the investigated process parameters the liquid flux showed a sufficiently high thickness over the pool but in general it can be stated the liquid flux thickness was enhanced when:

• Immersion depth of the SEN was lower (here lower than 100 mm). • Casting speed was higher (here higher than 0.9 m/min). • Port exit angle of the SEN was directed towards the interface steel melt/liquid flux.

The l iquid f lux t hickness w as l ow for a n i mmersion de pth o f 160 mm an d a cas ting v elocity of 0.5 m/min, but sufficiently high for most of the investigated operational parameters. BFI found f rom the physical s imulations and numerical computations limits for the cr itical variables investigated changes inside which a regular casting process was guaranteed. CRITICAL V ELOCITY - According to the CSM experience, critical velocity values r isky f or s ome defects occurrence are: About 0.35m/s at meniscus; higher values ease the slag-steel emulsification [32] About 0.30m/s at hot spot; higher values ease the shell ‘washing’, up to break-out risks [33]

HEAT FLUX D IFFERENCE - The be haviour of a t hird CAS steel h as b een co nsidered t o b etter support the shape of the empirical relationship hypothesised. The third steel of interest in terms of ghost lines is t he C AS 4 10, wh ose ch emical co mposition an d ch aracteristic t emperatures ar e r eported i n Tables 6-1 and 6-2. The ghost line defects of a t est heat of this steel grade are listed in Table A-10 in Appendix.

Table 6-1. Chemical compositions of the third steel considered, related to the compositions of the two main

steels.

Steel grade Chemical composition [wt %]

C S P Si Mn Cr Ni N

CAS F304L1 0.02 0.0225 0.04 0.20 1.25 18 10 0.045

CAS 420A7 0.20 0.025 0.03 0.40 0.50 13 - -

CAS 410 0.11 0.023 0.03 0.40 0.55 12 0.5 0.05

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Table 6-2. Critical temperatures of the third steel considered, related to the compositions of the two main steels.

Steel grade Characteristic temperatures [°C]

Tliq ZST LIT Tsol

CAS F304L1 1453 1422 1409 1393

CAS 420A7 1492 1444 1413 1367

CAS 410 1493 1459 1440 1401

Referring t o Figure 6-6, t he Q∆ peak v alue i s 0 .30MW/m2 in s teel F 304L1, 0. 34MW/m2 in s teel 420A7 and 0.41MW/m2 in s teel 4 10. From t he experimental observation o f “ghost lin e” d efectology only on this set of s teels, i t can be deduced that the cr itical value of Q∆ is the one measured wh ile casting steel F304L1 i.e. 0.30MW/m2.

Figure 6-6. Q∆ evolution along the mould height.

The trend of Q∆ along the mould height is different among these three steels considered. Then a more refined critical variable could take into account not only the Q∆ peak value but also its evolution.

Evaluation of centreline segregation parameters (porosity, mushy liquid relative flow rate (Dunaferr)

The question which arises at this point is that what are the optimum values of these functions from the viewpoint o f centreline s egregation? The acc eptance l evels o f s egregation p arameters we re s everal times in the focus at DEFFREE meetings. Parameters developed for characterising the inner quality of the cast product (porosity level, mushy liquid flow rate) can change in a relative wide range depending on chemistry, c asting c onditions and roll s ettings. It must b e d efined wh ich l evels can b e t aken into account the slab as a “defect free” product.

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In g eneral t he l ower t he p orosity l evel t he b etter t he i nner q uality, s o the c asting t echnology s hould provide porosity level as low as possible. According to the plant measurements and modelling results (Task 5. 6) s labs w ith centreline p orosity l ower th an 6 m m2 can b e accep ted as a r ealistic t hreshold value.

Concerning the mushy liquid movement, theoretically zero flow rate should be optimal over the whole length of the upper part of the mushy section. The statistical analysis of industrial data – which were used for the development of LMI model – established the estimation method of porosity parameter, but not of th e mushy flow rate c alculation. I t f ollows f rom th is that it is very d ifficult to evaluate quantitatively th e f low r ate le vel f rom t he p oint o f v iew of centreline s egregation. According t o t he literature and to our own experiences only qualitative approach can be applied. The flow rate must be as low a s po ssible, but s hould be m ore or l ess ho mogenous i n t he m ushy a rea i n t he centreline. F rom theoretical and practical points of view, small positive values of mushy liquid movement seem to be the best, resulting in slight squeezing out of liquid from the mushy area.

More than 40 casting cases were analysed from this point of view. In the half of the cases besides the dataset o f t echnological p arameters a nd m odelling r esults t he s ulphur pr int a nd m acroetching photographs of the slabs were also available (see also Task 5.4). The centreline s egregation in s labs d evelops in a c omplex w ay; it is c onn1ected p artly t o t he macrosegregation an d p artly t o t he s hrinkage o f s olidifying m elt wh ich ar e i nfluenced b y a l ot of technological features. According t o l iterature d ata an d t o our r esults, t he s hrinkage p orosity an d deformation of slab in the last stage of solidification play the main role in the formation of centreline segregation. The volume change due to solidification and the de formation of s lab shell i nfluence the liquid movement in the mushy zone as well. Among the casting parameters the supporting roll settings in t he m ushy a rea i s t he m ost i mportant i nfluencing f actor concerning t he f ormation of centreline segregation, but all of the casting parameters can affect this process (chemical composition, superheat, casting r ate, s econdary co oling s ystem, rigidity of th e c asting m achine, r oll b earings, r oll s ettings, eccentricity of rolls, b ulging et c.) t o some e xtent. As a r esult o f t hese p rocesses t he centreline segregated p art o f the s lab wi ll h ave a d ifferent ch emical composition compared t o t he av erage composition and/or it will contain shrinkage holes. AALTO simulated the casting trials of DUFERCO and CAS. DUFERCO and CAS classified heats to be s imulated w ith g ood a nd ba d qua lity and t he i ntension w as t o s tudy, w hether t here w ere s ome differences b etween t hem. I DS cal culations s howed t hat during s olidification o f b oth CAS and DUFERCO steels Nb(C,N), V(C,N) and AlN precipitations can form which increases the cracking risk. Those compounds s tart to form between 700-1000°C depending on s teel composition. By controlling cooling the formation of these elements can be decreased when surface and corner temperature does not fluctuate or c ool s lowly d own in t his t emperature r ange. Heat t ransfer s imulations s howed that there were only very small differences in surface temperatures with good and bad quality heats. However, the absolute corner temperatures changed fast after the mould and dropped down to 800°C. So according to the simulations a softer cooling could be tested in the first two meters from the mould exit. DUFERCO had good results on steel quality when they decreased secondary cooling with their crack sensitive steel grades. Steel grade 420A7 of CAS had problems wi th subsurface cracks and the average d istance of crack from t he b illet s urface was 1 4-15 m m. According t o t he he at t ransfer s imulation a nd t heory behind crack formation the place at the caster where the cracks had been formed was around 1 m from meniscus, wh ich i s j ust t he l ocation wh ere s urface t emperatures d rop r apidly t o r ise ag ain, wh ich increases the thermal stresses. Task 6.3 Elaboration of guidelines for the extension of the new on-line model for detection and controlling the casting process to other continuous casting machines (all partners) BFI concentrated in its work on process parameters influencing the general fluid flow in the mould, the liquid f lux t hickness ab ove t he melt p ool o f s lab cas ter an d t he wav e h eight at t he i nterface. T hese topics were related to a n umber of defects mainly influencing the product quality and guidelines were elaborated to avoid or at least minimize the number of defects.

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When considering the f luid f low BFI found f rom its in vestigations, th e general f low s tructure in th e mould was d irectly influenced by the geometry o f the SEN. The investigated SEN geometry used b y DUNAFERR with two ports generates a flow structure inside the mould of the so called “double roll” typ. This flow structure is said to guarantee a stable casting process when critical process parameters are controlled to be inside the range of a fixed operating window. It was necessary that the velocities do not excess a critical value at the steel melt/liquid flux interface. The critical velocity was avoided for

• High immersion depth of SEN • Low casting speeds • SEN ports directed away from the interface of the steel melt/liquid flux

It was very important to guarantee a s ufficiently h igh l iquid f lux thickness for defection f ree cas ting. Many d efects were r elated to an in sufficiently h igh liq uid f lux thickness. As a av erage value f or t he liquid f lux th ickness 13 mm was found to be necessary. This value comes f rom measurements in the plant at casters where a good quality was produced [12]. In contrast to the fluid flow related defects, where it was necessary to guide the inlet melt flow away from the interface and keep the velocities low, it was necessary for a sufficiently high liquid flux thickness that the melt is directed to the interface to transport h ot s teel m elt t o th e in terface o f th e s teel melt/liquid f lux. T han it w as g uaranteed th at sufficiently high amount of energy is transported to the interface to guarantee a melted liquid flux

• Low immersion depth of SEN • High casting speeds • SEN ports redirected to the interface of the steel melt/liquid flux

It was seen from the investigation that what was good for the fluid flow was not good for a s ufficient high liquid flux thickness. But it also was shown in the investigations that a sufficiently high liquid flux thickness was g uaranteed at t he cas ting co nditions wh ere t he f luid f low g uarantees d efection f ree casting for the DUNAFERR caster. It must be adhered that the s lab casters have a very wide range of possible SEN geometries and s lab sizes itself. So that the precise process parameters must be investigated individually for each SEN and caster geometry. The here named limits and guiding rules were evaluated for a individual caster design and only can give crude values with response to any caster with a two port SEN of similar mould size. General flow structures differ from the type “double roll” led to completely different flow behaviour at the interface steel melt/liquid flux and therefore to a ch ange in heat t ransportation of the steel melt to the liquid flux and a completely different liquid flux thickness. The f lowchart for t he o nline c omputation (CSM) of t he h eat f lux p rofile f rom t he p rocess d ata i s sketched i n Figure 6-7. Af ter measuring an d s toring i nstantaneous d ata f rom p rocess, a hypothetical heat flux profile is proposed as input to the thermal computation: the 1st attempt heat flux profile 0stepq

is chosen to be equal to the measured average mould heat flux q uniformly at all the N instrumented mould rows.

Niqq stepirow ,,1,0 == (25)

From the heat f lux p rofile, the t emperature at each quota 0step

irowT and the corresponding relative gap

with the acquired thermal profile ( )iTCT are computed; these to update the heat flux profile for a further thermal computation step if that gap does not fit the chosen tolerance criterion:

( )( )

−−⋅=+

iTC

iTCj

iji

ji T

TTqq 11 (26)

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The m entioned ap proach i s g eneral, i ndependent f rom t he c asting s cenario i nvolved, s o i t can b e extended to the casting machines and due to its specific feature, used for detection and controlling every casting process.

Figure 6-7 - Flowchart for the computation of the heat flux profile. New concept for on-line q uality control is g iven b y LMI model of DUNAFERR and OBUDA. The empirical relationships built in the LMI model based on wide spread statistical analysis was performed earlier. The validity of this relationship seems to be independent on the individual casting machine. It follows from this s tatement that the extension of the model to other continuous caster machines does not n eed t he ch ange o f t he cal culation m ethod i n g eneral. On ly s light m odifications i n t he m odel because of the design and size of the different machines must be performed. According t o our e xperiences t he r eliability of LMI model de pends o n t he r eliability o f i nput da ta. Special attention should be paid for the generation of input data set as follows:

• Temperature distribution inside the slab (Tempsimu or other heat transfer models can be used) • Temperature dependent material data (IDS, JMatPro or other) • Reliable data concerning the real position of supporting roll (roll checker data), • Reliable data concerning the real eccentricities of supporting rolls (individual measurement of

eccentricity under appropriate load), • Estimated bulging data (BOS or other), • Casting parameters (casting speed, superheat, cooling intensities, etc.) • In case of non-steady state castings the time-dependence of the casting parameters

LMI model can be applied not only steady, but non-steady-state casting cases for analysing the effect of casting parameters and roll settings on the inner quality. Figure 6-8 summarises the data necessary for LMI calculations.

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Figure 6-8. Introduction of LMI mathematical model. CastManager on-line casting simulator The CastManager on-line model (Figure 4-2) of AALTO can be adapted to other casters, as well. First the cas ter h as t o b e s et up in t he T empsimu s teady-state m odel, r equiring d ata o f caster geometry, cooling zo nes, l ocation o f n ozzles an d r olls an d wat er i ntensities through t he no zzles on t he s trand surface. For CastManager process data; casting speed, cooling waters etc. are needed. When used as an on-line model the p rocess data has to c ome au tomatically in the defined form to the m odel from the automation s ystem of t he caster. C astManager can b e u sed o ff-line t oo, a s a t ool f or s tudying t he different casting cases and casting parameter changes. From IDS and ADC models solidification, phase transformation, in clusions a nd p recipitations a re o btained. Through c oupling I DS a nd A DC t o t he CastManager, the model calculates phases formed and phase fractions on -line during casting. Quality indices can be calculated wi th IDS (combined wi th ADC) model, but the indices are not yet d irectly coupled to the CastManager. This is planned to be done in the near future. Then the model will able to show on-line the appearance of the quality risks during real casting. These quality indices are now used off-line determining the quality of the steel.

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2.4 Conclusions of the project The m ain o bjective o f t he p roject was t o de velop a ne w m odelling ba sed o ptimisation a nd quality control s ystem f or c ontinuous casting. The new concept is based on critical p arameters a ffecting t he steel quality and finding safety ranges for the parameters in order to ensure good quality in continuous casting. These critical parameters were obtained both from casting experiments and from mathematical models. Of in dustrial p artners in t he p roject, DUNAFERR produces car bon s teels wi th v ertical s lab cas ters whereas DUFERCO produces carbon s teels and CAS stainless and special s teels wi th billet c asters. They performed casting trials and analysed the quality of the steels in the heats. Steel grades, data of the casters and process parameters were collected and delivered to CSM, BFI, AALTO and OBUDA for modelling work. Within the project DUNAFERR and CAS equipped their moulds with thermocouples and DUFERCO installed an automatic mould powder feeding system. DUNAFERR carried out cast trials to study the effects of process parameters on centreline segregation and on surface quality. Two typical surface defects were found, transversal and star crack. By coating a mould with nickel surface quality problems of the slabs were greatly decreased. All important process data wer e recorded f or t he validation of t he m athematical m odels. Evaluating the co llected d ata i t became possible to demonstrate the e ffect of superheat and cas ting speed modification on the mould temperature distribution and on the s trand surface temperature. DUNAFERR also modified the roller settings o f t he cas ter t o f ollow b etter t he n atural s hrinkage o f s teel. T his d ecreased cen treline segregation severity remarkably. CAS studied subsurface cracks which often lead to ghost line defect in rolled products. In consequence of this project, CAS was able to reduce subsurface cracks by controlling process parameters within the critical l imits d efined. T he l owering o f r ejected p roducts af ter h ot r olling i s a clear ev idence o f t he benefits obtained through this project. DUFERCO investigated transversal cracks, (oscillation marks and depressions) and macrosegregation in b illets. I n th e c asting e xperiments th ey te sted various secondary c ooling pa tterns w ithin different steel grades and found appropriate water flow rates for the steel grades. Also new mould powders were selected for certain grades. Better quality was obtained with crack sensitive grades mostly by decreasing the amount of waters and with high carbon steel by applying hard cooling on their second cooling zone to d ecrease m acrosegregation. Up setting t ests o n wi re r ods ( crack s ensitive grades) showed t hat the rejection decreased after decreasing secondary cooling. A variation of d ifferent phenomena was s imulated wi th fundamental and semi-empirical models. For validating the models among others, physical fluid flow simulations, physical stress-strain simulations, and mould t emperature measurements wer e c onducted. I n a ddition, literature data was u sed. In t he following are listed the models applied in the project: BFI

1) CFD m odel f or s teel/slag s ystem in th e m ould f or c alculating th e d istribution of liq uid p ool thickness of casting powder and velocity field along the perimeter as well as the height of the steel and liquid flux wave

2) A coupled CFD model for heat transfer and fluid flow for the strand for calculating temperature and velocity distribution all along the strand

CSM

1) Liquid po ol m odel for c alculating t he t hickness o f l iquid, s intered a nd powder l ayer of t he casting powder on meniscus

2) Liquid flux in filtration mod el, w hich provides a s olution f or th e v elocity and p ressure f ields inside th e mould-shell g ap. T he m odel al so es timates t he shape o f t he m eniscus an d, as a consequence, simulates the formation of the oscillation marks.

o To understand the origin of the defects connected to lubrication problems 3) Steady-state 3D thermo-mechanical model for the mould

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o Temperature and strain distribution of the mould 4) Transient 2D thermo-mechanical model for solidification of liquid steel in the mould

o Temperature and strain distribution in the solidifying shell 5) Inverse model for calculating heat f lux difference between the midface and the corner of the

billet from the mould temperature measurements. o As an off-line model: a tool to find appropriate casting speed, casting powder and the

mould taper for various steel grades to achieve better quality o As a n o n-line m odel: Heat flux c ould be c omputed o n-line s ubmitting th e l ogged

temperature profiles along the thermocouple lines to a t hermal computation iteratively till th e c omputed th ermal f ield f its th e m easured f ield. In p rinciple th is c ould b e coupled t o C astManager m odel wh ich h as a s eparate m ould h eat t ransfer cal culation model and uses earlier defined h-gap curve.

DUNAFERR together with subcontractor OBUDA

1) Dunaferr model o For calculation of liquid pool depth and its shape.

2) Columnar to equiaxed transition model o CET model based on thermal calculation data and experimental results from real casts

3) Mathematical model for determination of stress – strain history of surface and subsurface area of solidifying slab for predicting of surface and subsurface cracks of cast slabs (“accumulated damage”)

4) On-line 2D transient centreline segregation model LMI (=Liquid Motion Intensity) o Besides h eat t ransfer, t he model t akes i nto account de formation o f s olid s hell b y

calculating s hrinkage a nd bul ging a nd t akes c ognisance o f s upport r oll po sitions, eccentricies etc., factors which affect the formation of centreline segregation.

5) Casting case analyser software AALTO

1) Solidification and phase t ransformation model IDS ( includes austenite decomposition module ADC)

o Solidification, phases, phase fractions, inclusions, precipitations, material data 2) 3D steady-state heat transfer model for casting, Tempsimu

o Temperatures, i sotherms i n s teady-state a nd s etting u p the caster g eometry al so t o CastManager

3) On-line d ynamic 3 D h eat t ransfer m odel f or cas ting, CastManager, ( both t he s trand a nd t he mould modules) coupled with IDS and ADC

o Temperatures, isotherms and phases along the whole strand Several critical features and parameters for s teel quality were defined both from the industrial casting trials a nd fro m the modelling r esults. In g eneral, f luid f low r elated p arameters, cr acking i ndices for solidification and heat transfer and segregation severity parameters were defined. The specified critical parameters are collected in Appendix 3 (also in different tasks). On-line models Safety ranges for the critical parameters obtained from fundamental models and casting experiments are used off-line as in itial safety window inside wh ich the parameters have t o s tay during cas ting. If the critical f eature was s uch t hat i t can not b e co ntrolled o n-line dur ing c asting, fo r e xample, s urface velocity of liquid in the mould, this feature was expressed as a function of casting parameter which can be controlled and modified during casting, for example casting speed. As a summary, three on-line models were developed in the project (descriptions above):

• On-line 2D transient centreline segregation model LMI • On-line dynamic 3D heat transfer model CastManager • On-line inverse mould heat flux difference model

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All the models can b e ap plied t o o ther cas ters t o s imulate d ifferent phe nomena dur ing c asting a nd finding safety ranges for the defined parameters. There was a go od co-operation o n s olving bo th m odelling a nd e xperimental i ssues between t he industrial pa rtners a nd t he pa rtners w ho m ade t he m odelling w ork i n o rder t o find o ut c ritical parameters and safe operation ranges to ensure the best possible steel quality. 2.5 Exploitation and impact of the research results The major results of the p roject a re the three developed t ransient on-line models, LMI, CastManager and t he inverse mould heat flux difference m odel and the critical p arameters determined for s teel quality. LMI and CastManager simulate heat transfer during dynamic casting conditions, LMI model in 2D and CastManager i n 3 D. T he b oth m odels can s imulate h eat t ransfer i n billet, b loom a nd s lab c asting, temperatures and isotherms al l along the caster. LM I model is especially capable for s lab casting and for p redicting centreline s egregation. The mould heat f lux d ifference m odel i s b ased o n i nverse approach and heat flux could be computed on-line submitting the logged temperature profiles along the thermocouple lin es to a th ermal c omputation ite ratively until the c omputed th ermal f ield f its th e measured f ield. I n p rinciple t his co uld be co upled f or ex ample t o C astManager m odel wh ich h as a separate mould heat transfer calculation model and uses earlier defined h-gap functions. All of these models are general and can be applied to other casters, as well. Through c asting e xperiments a nd m odelling r esults i ndustrial pa rtners c ould de crease t he a mount o f defects and improve as-cast steel and product quality by running the casting processes within the safe limits of the critical parameters. This proves the significance and usefulness of the critical parameters defined in the project and these parameters and also safety limits can bring benefit also to other s teel plants. Critical features which are derived from the mould fluid flow simulations in slab casting can be adapted also to other slab casters. These modelling results give possibility to design SEN, determine immersion depth and determine safety ranges for casting speed to assure good steel quality. The results of the project are planned to be published in conferences and journals. Publications:

1. Reger M, Vero B, Csepeli Zs, Jozsa R: Prediction of Centerline Segregation of CC Slabs, In: 7th European Continuous Casting Conference. Düsseldorf, Germany, Düsseldorf: 2011, pp. x1-x9.

2. Reger M, Vero B, Cepeli Zs, Szabo Z, Józsa R, Kelemen T: Effect of Supporting Rolls Settings on the Inner Quality of Cast Slabs, VIIIth. OATK Conference, Balatonkenese, Hungary, 9-11 oct. (2011)

3. Reger M, Kytönen H, Vero B, Szelig A: Centerline Segregation of CC Slabs, MATERIALS SCIENCE FORUM 649: pp. 461-466. (2010)

4. Réger M: Estimation of Strains and Stresses Developed on the Slab Surface, In: XVth FMTÜ Conference, Cluj-Napoca, Romania, 25-26 March,.2010.03, pp. 255-258

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List of Figures and Tables

Figures Figure 1 -1. Dependency o f s teel a ) s urface velocity and b ) f ree s urface wave height on casting s peed. Mould: 1.75mX0.175m. Immersion depth: 140 mm. SEN type: sen1, sen1+5mm, sen1+10mm. Nozzle port: 5X(45,50,55). Nozzle angle: -10, -15, -20 degree. Casting speed: 1.40, 1.55, 1.70 m/min. Figure 2-1. Sketch of the simulation of powder addition in CSM “Liquid pool model”. Figure 2-2. First simulation with CSM enhanced “Liquid pool model”, including powder additions. Figure 2-3. Comparison between average and step density behaviours versus void ratio. Figure 2 -4. The computed and measured velocity profile a t the interface, in the centre l ine of the mould, for a casting speed of 0.9 m/min and an oil film thickness of 60 mm. Figure 2-5. Liquid fraction of the mould powder computed with the numerical model temperature field and liquid fraction b) velocity at the interface. Figure 2 -6. Approach t o m odelling of f luid-dynamics i nside t he m ould-shell g ap a nd c alculation of m eniscus shape. Figure 2 -7. R esults o f C SM “ Liquid f lux i nfiltration m odel”. The os cillation m ark pr ofile i s t he t rajectory of meniscus point in contact with the mould when the mould speed is its maximum upwards. Figure 2-8. Physical Perspex® model of the mould with PIV measurement system. Figure 2-9. Flow visualisations of the interface for different casting speeds, oil film thickness 30 mm, a) VC = 0.6 m/min, b) VC = 0.9 m/min, c) VC = 1.2 m/min, d) wave heights for three immersion depth of the SEN 1. Figure 2-10. Measured wave heights at the interface water/oil in the centre plane for different casting speeds, oil film thicknesses and immersion depths of a) SEN 1and b) SEN 2. Figure 2 -11. M easured v elocities i n t he c entre plane o f the m ould (one s ide) f or S EN 1 ( = 0°), imme rsion depths 120 mm, and for a casting speeds of a) vC = 0.6 m/min, b) vC = 0.9 m/min, c) vC = 1.2 m/min. Figure 2 -12. M easured velocity m axima a t the s urface f or d ifferent i mmersion d epth i n d ependence f rom t he casting speed for SEN 1 and SEN 2. Figure 2-13. PIV measurements of the two-phase flow water/oil in the centre plane of the mould and SEN 2 for a casting speed of 0.9 m/min and an immersion depth of 120 mm. Figure 2-14. Surface temperature distribution in an industrial case. Figure 2-15. Sketch of the slab with the modelling volume and important directions Figure 2-16. Cooling curve of an individual surface point. Figure 2-17. Analysis of the cooling curve. Figure 2-18. Liquid pool depth and shape in the X2Z2 plane. Figure 2-19. Liquid pool depth and shape in the Y2Z3 planes. Figure 3-1. Inverse model for the derivation of heat flux. Figure 3-2. Geometry and mesh of the mould FEM model. Figure 3-3. 2D steel FEM model, 5200 8-node generalized plane strain elements. Figure 3-4. 3D representation of the 2D steel model evolution. Figure 3-5. Displacement map on the outer shell surface, the highest shrinkage is around the corner. Figure 3-6. Temperature and velocity distribution along the complete strand with regions of interest zoomed out. Figure 3-7. Sketch for the explanation of porosity and flow calculations. Figure 3-8. Flow rate distribution of mushy liquid for different tapers. Figure 3-9. Flow rate distribution of mushy liquid for different tapers. Figure 3-10. Nomogram for the thermal gradient threshold determination. Figure 3-11. Input and output data of IDS model. Figure 3-12. On the left: Fe-C phase diagram, on the right: Fe-C phase diagram with boron addition from 0.001% to 0.003%. Figure 3-13 a) Calculated oxygen solubility in liquid Fe-Al alloys at 1600°C, together with experimental data points.b) Calculated isothermal section of the Fe-Ti-O system at 1300°C. Figure 3-14. Accumulated damage functions calculated for a real casting case. Figure 4-1. CastManager results in different user interfaces and process data for the simulation. Figure 4-2. On-line simulator construction for quality prediction of the cast strands. Figure 5 -1. T op v iew ( a) a nd s ide v iew ( b) of t he C AS instrumented m ould. c ) Thermocouples p ositioning. (“intradosso” = inner or loose side; “estradosso” = outer or fixed side; “lato” = side). Figure 5-2. Mould at DUNAFERR equipped with thermocouples (wide side). Figure 5-3. Calculated heat flux values for the right part of a wide side of the mould Figure 5-4. An example of melt level variation in a mould during casting. Figure 5-5. a) Distribution of the thermocouples at 120mm from meniscus and the corresponding temperature time evolution. ). Distribution of the thermocouples at 180mm from meniscus and the corresponding temperature time evolution.

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Figure 5-6. 160*160mm2 mould thermocouple signals from F304L1 heats (left) and 420A7 heats (right). Figure 5-7. CAS steel sizes 160*160mm2 a) steel F304L1: absence of observed defects; b) steel 420A7: red-evidenced defects in the off-corner regions. Figure 5-8. Steel CAS F304L1, heat 72887: a) surface straight-longitudinal defect; its depth is 0.08-0.15mm; not continuous; rods affected 5/13; b) locations on the rods. Figure 5-9. Typical internal crack in billets of martensitic peritectic resulphurised 420A steel. Figure 5-10. Steel CAS 420A7 heat 073012: surface straight-longitudinal defect; its depth is 0.08-0.09mm (type 1) and 0.35mm max (type 2); not continuous; rods affected 4/4. Figure 5-11. Typical surface defects at DUNAFERR a) transverse crack, b) star crack. Figure 5-12. The effect of superheat on the surface temperature of the strand. Figure 5-13. Evolution of defect: a) billet surface edge, b) cross section (billet) c) wire rod (cross section). Figure 5-14. Macroetched billet samples with cooling menu C and H. Figure 5-15. Macroetched billets of steel grade 19MnB4 (cooling menu H). Figure 5-16. SEM investigations on cracks over 10 mm on billet surfaces in steel grade 19MnB4. Figure 5-17. SEM investigations on cracks over 3 mm on billet surfaces in steel grade 19MnB4. Figure 5-18. Cracks on the C-Mn-Ti grade billets with the secondary cooling menu C. Figure 5-19. a) Hard cooling in zone Z1 and b) Macroetched cross-section of a billet (menu F). Figure 5-20. Example of billet section from which samples were derived for EDS analysis. Figure 5-21. An example of CSM EDS analysis of CAS samples of steel F304L1. Figure 5-22. Baumann print of the slab cross-section. Figure 5 -23. C hemical c omposition a s the f unction o f the di stance from c entreline.The b ackground i s t he Baumann print of the investigated slab. Figure 5-24. Numerically computed temperature distribution at the centreline, narrow side, wide side and corner of the strand. Figure 5-25. Flowchart of the calibration technique for the "Liquid pool model". Figure 5-26.a) Experimental device for the melting rate curve measurement (used in ECSC project 7210.PR/273, June 2004). b ) S imulation of the e xperimental de vice - Numerical r esult obtained a t the e nd o f t he r ecursive procedure to calibrate the value of kinetic parameter a Figure 5-27 “Liquid pool model” numerical results. Figure 5-28. Evolution of the heat flux profiles along the casting lines; a) heat 72142-72143 of steel CAS F304L1; b) heat 72299-72300 of steel CAS 420A7. Figure 5-29. Agreement of the thermal field between acquisition and computation (FDM model). Figure 5 -30. M ould t emperature f ields a t mid-face a nd 2 0mm f ar f rom t he c orner. Comparison between t he thermocouple acquisition and the results from computation; a) heat of steel CAS F304L1; b) heat of steel CAS 420A7. Figure 5-31. Setting of the original and the modified supporting roll gaps along the strand. Figure 5-32. Calculated porosity levels in the case of the original and the modified roll settings. Figure 5-33. Mushy liquid flow rates in the centreline region with the original and the modified roll settings. Figure 5-34. Etched cross-sections of the centre area of the cast slabs a) on the left the original taper and b) on the right the modified taper. Figure 5-35. Heat transfer values used in Tempsimu and CastManager models. Values from experiments in [29-31]. Figure 5-36. Indication of possible correlation between segregation index and process parameters. Figure 5-37. FEM profiles of interest for identifying the critical parameters. Figure 5-38. Steel level variation in the mould and effect of age of sliding gate. Figure 5-39. Influence of operating parameters on up-setting tests for cold-headed steel grade. Figure 5-40. Ferrite potential tendency indices. Figure 5-41. Schematic presentation of quality index QISTR. Figure 5-42. a) Background of quality index QISOL. b) Graphical presentation of quality index QISOL and c) Effect of cooling on QISOL. Figure 5-43. a) Background of quality index QISHE b) Graphical presentation of quality index QISHE.and c) Effect of cooling on QISHE. Figure 5-44. a) Background of quality index QIGRA. b) Graphical presentation of quality index QIGRA and effect of cooling on QIGRA. Figure 5-45. Background of quality index QICOM. Figure 5-46. Graphical presentation of quality indexes QICOM and QIADC. Figure 5-47. Background of quality index QIADC. Figure 5-48. Background of quality index QIHAR. Figure 5-49. Distorted profiles of inner surface of the mould’s cross-section at different levels below the meniscus (deformation enlarged by a factor 100; e.g. deformation = (0.02/100)m = 0.0002m=0.2mm); a) heat of steel CAS F304L1; b) heat of steel CAS 420A7. Figure 5-50. Temperature maps on the outer shell surface, showing the presence of hotter off-corner regions; a) heat of steel CAS F304L1; b) heat of steel CAS 420A7.

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Figure 5-51. Displacement maps on the outer shell surface, showing the highest shrinkage around the corners; a) heat of steel CAS F304L1; b) heat of steel CAS 420A7. Figure 5 -52. a ) Liquid a nd solid de lta-ferrite f raction dependence on temperature in s teel CAS F304L1; b) t he same for steel CAS 420A7; c) linear thermal expansion coefficient comparison between the two steels. Figure 5-53. Steel-to-mould gap maps – a) heat of steel CAS F304L1; b) heat of steel CAS 420A7. Figure 5-54. Both the steels - Evolution along the mould height of the heat flux (a), the surface temperature (b) and the gap (c) profiles between mid-face and corner. Figure 5-55. Macro etched billet sections. a) steel CAS F304L1, example of defect-free sample; b) and c) CAS steels 420A7 and 410, examples of ghost-line defect in the off-corner. Figure 5-56. Hot-tearing index field on the steel billet section at the mould exit. Figure 5-57. Numerically computed liquid flux thickness and wave heights at the meniscus of the mould with an immersion depth of 120 mm and a mould powder thickness of 60 mm for different casting speeds a) 0.5 m/min b) 0.7 m/min c) 0.9 m/min Figure 5-58. Three dimensional temperature distribution along the strand (for better representation compressed in casting direction), a) view from outside, b) view from centreline. Figure 5 -59. Temperatures at the centre, the c orner, the n arrow a nd t he w ide s ide o f t he s lab for di fferent immersion depth of the SEN a) 80 mm, b) 120 mm, and c) 160 mm. Figure 5-60. Microsegregation of chemical elements in F304L1 and 420A7 steel grades. Figure 5 -61. Midface and corner temperatures of steel grades F304L1 (heat 72888) and 420A7 (heat 73428) a t CAS. Figure 5-62. Liquidus and solidus temperatures of steel grades F304L1 (heat 72888) and 420A7 (heat 73428) at CAS. Figure 5-63. Midface and corner temperatures in heats 73237 and 73428 of CAS (0-7m). Figure 5-64. Liquidus and solidus isotherms in heats 73237 and 73428 of CAS. Figure 5 -65. D ynamic s imulations of h eat 7342 8 of steel g rade 420A7 of C AS with c asting s imulator CastManager. Figure 5-66. Midface and corner temperatures of heats 54795 and 54797 (0-20m). Figure 5-67. Midface and corner temperatures of heats 54795 and 54797 (0-7m). Figure 5-68. Midface and corner temperatures of heats 56319 and 56317 (0-20m). Figure 5-69. Midface and corner temperatures of heats 56462 and 56708 (0-20m). Figure 5-70. Liquidus and solidus isotherms of heats 54797 (casting speed 2.20 m/min, secondary cooling water: zone1: 1.7 m 3/h, zone2: 1.7m 3/h, zone3: 1.2m 3/h) and 56317 ( casting speed 1.8 5 m/min, secondary c ooling water: zone1: 1.5 m3/h, zone2: 1.5m3/h, zone3: 1.1 m3/h). Figure 5 -71. M idface a nd c orner temperatures of heats 5479 7 ( casting s peed 2. 20 m /min, s econdary c ooling water: z one1: 1.7 m 3/h, z one2: 1.7m 3/h, z one3: 1.2m 3/h) a nd 5631 7 ( casting s peed 1.85 m /min, s econdary cooling water: zone1: 1.5 m3/h, zone2: 1.5m3/h, zone3: 1.1 m3/h). Figure 5 -72. D ynamic s imulations of he at 54797of s teel g rade 20MnB4 of D UFERCO w ith c asting s imulator CastManager ( casting s peed 2 .20 m /min, s econdary c ooling water: z one1: 1.7 m 3/h, zone2: 1.7m 3/h, zone3: 1.2m3/h) Figure 5 -73. Dynamic s imulations of heat 56317 of s teel grade 20MnB4 of DUFERCO with c asting s imulator CastManager (casting speed 1.85 m /min, secondary cooling water: zone1: 1.5 m 3/h, zone2: 1.5m3/h, zone3: 1.1 m3/h) Figure 6-1. Numerically computed liquid flux thickness (minimum) for different casting speeds. Figure 6-2. Numerically computed wave height (maximum) for different casting speeds. Figure 6-3. Numerically computed velocity at the steel melt/liquid flux interface (maximum) for different casting speeds. Figure 6-4. Input and output data of the Casting case analyser software (case no. 1) Figure 6-5. Input and output data of the casting case analyser software (case No. 20). Figure 6-6. Q∆ evolution along the mould height. Figure 6-7 - Flowchart for the computation of the heat flux profile Figure 6-8. Introduction of LMI mathematical model.

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Tables Table 1-1. Chemical compositions of the CAS reference steels. Table 1-2. Typical chemical compositions of steels produced at DUNAFERR. Table 1-3. Chemical compositions of the steel grades DUFERCO in this project. Table 1-4. Determined critical parameters and safety ranges for them. Table 1-5. Influencing factors to the main surface defects. Table 2-1. Main input data for the “Liquid pool model”. Table 5-1. Surface quality index determined melt level Table 5-2. Steel CAS F304L1 - Main casting parameters, common (on average) to all the heats considered. Table 5-3. Steel CAS 420A7 – Main casting parameters, commons (on average) to all the heats considered. Table 5-4. Comparison of surface defects on slabs cast in the moulds with and without Ni-coating. Table 5-5. Steel compositions of example heats 41334 and 69469 in C-Mn-B-Ti steel grade. Table 5-6. Casting parameters of heats 41334 and 69469 of steel grade C-Mn-B-Ti and calculated Ferrite potential (FP) values. Table 5-7 Secondary cooling menu C and H of DUFERCO (casting speed 2.2 m/min). Table 5-8. A summary of the casting operation and quality of the steel grade 20MnB4 at DUFERCO. Table 5-9. A summary of the casting operations and quality of the steel grade 30MnB4. Table 5-10. An example composition of peritectic C-Mn-Ti steel grade. Table 5-11. Casting parameters of C-Mn-Ti grade and calculated Ferrite potential (FP). Table 5-12. Secondary cooling menus C and A of DUFERCO (casting speed 2.2 m/min). Table 5-13. Composition of the heat with hard cooling (68910) and the heat without hard cooling (64958). Table 5-14. Secondary cooling menu C and F of DUFERCO (casting speed 2.2 m/min). Table 5-15. Segregation index of billet specimens of heats 68910 and 64958 and the reduction of area, Z %, of wire rod (diameter 13 mm). Segregation index: 1 = the best, 3 = the worst), Z (%) = ROA, reduction of area. Table 5-16. Chemical composition of the investigated steel. Table 5-17. Critical parameters and safety ranges derived from the fluid flow investigations of BFI. [38,39] Table 5-18. Critical parameter: porosity level in the centre part of slab. Table 5-19. Critical parameter: Relative flow rate of mushy liquid in the centreline of slab. Table 5-20. Impact of 3 factors to the up-setting tests results. Table 5-21. Compositions of the studied heats of steel grade F304L1. Table 5-22. Compositions of the studied heats of steel grade 420A7 of CAS. Table 5-23. Quality determination of the heat CAS studied and simulated. Table 5-24. Solidification calculations of the studied heats of steel grade F304L1 of CAS (IDS model). Table 5-25. Solidification calculations of the studied heats of steel grade 420A7 of CAS (IDS model). Table 5-26. Quality indexes and phase fractions at 25°C in the heats of CAS. Table 5 -27. C ompositions of the studied h eats of s teel g rade 20 MnB4 w ith m ould p owder M elubir 3011 of DUFERCO. Heat 54795 good quality heat, 54797 bad quality heat. Table 5-28. Compositions of the studied heats of steel grade 20MnB4 with mould powder Syntherm GB 1022/M of DUFERCO. Heat 56319 good quality heat, 56317 bad quality heat. Table 5 -29. Compositions of the studied heats of steel grade 30MnB4 of DUFERCO. Heat 56708 good quality heat, 56462 bad quality heat. Table 5-30. Simulated heats of DUFERCO by AALTO. Table 5-31. Solidification calculations of the studied heats of steel grade 20MnB4 (IDS model). Table 5-32. Solidification calculations of the studied heats of steel grade 30MnB4 (IDS model). Table 5-33. Quality indexes and phase fractions at 25°C in the heats of DUFERCO. Table 5-34. Casting speed and secondary cooling of the heats 54797 and 56317. Table 6-1. Chemical compositions of the third steel considered, related to the compositions of the two main steels.

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[41] Monroe C., Beckermann C., “Development of a hot tear indicator for steel castings”, Material Science and Engineering A, 413-414 (2005), 30-36 [42] Yamanaka, A., Nakajima, K., Okamura, K. Critical strain for internal crack formation in continuous casting. Ironmaking and Steelmaking 22(1995)6 s. 508-512. LIST OF SYMBOLS C constant - Fr Froude number - h height m, mm k turbulent kinetic energy m²/s² l length m m mass kg q number of phase - Re Reynolds number - S source term - t time s T temperature K u,v velocity m/s We Weber number - Greek symbols α phase fraction - δ thickness mm ε dissipation m²/s³ γ interfacial tension N/m µ dynamic viscosity kg/ms ν kinematic viscosity m²/s ρ density kg/m³ Indices C casting critical indicates a critical value of a flow field variable liquid flux in the liquid flux layer of the mould powder melt melt tur turbulent w wave

133

Appendix 1 - Appendix Figures and Tables

a) b)

Figure A-1. Technical Drawing of the two investigated SEN`s a) SEN 1 with a port exit angle of 0°, b) SEN 2 with a port exit angle of -15°

Table A-1. Boundary conditions collected from DUNAFERR for the BFI CFD-simulation.

geometry slab size mould 1045 x 240 mm

cold 1045 x 230 mm length of the caster mould length is 600 mm

caster length is 10020 mm inlet inlet temperature 1555 °C super heat 30 °C casting speed 0,53 m/min melt steel grade 4d class DE 460 MLC Tsolidus 1486.9 °C Tliqidus 1525.1 °C primary cooling zone mass flow rate of cooling water 380 m3/hour temperature rise of cooling water around 3 °C temperatures of slab at the end of primary cooling zone

mid wide face: 1183 oC corner: 1000 oC centre line: 1555 oC

shell thickness at the end of primary cooling zone

solidus: 19,46 mm liquidus: 25,36 mm mid of wide face

secondary cooling zone mass flow rate of cooling water 1460 l/min = 87,6 m3/hour length of the cooling zone 9420 mm temperatures at the end of cooling zone aprox. 845 °C caster metallurgical length 9750 mm

80

120

50

80

80

120

50

80

15°

134

Table A-2. Chemical composition of steel grade S460ML (1.8838)

steel grade C Mn Si P S Al V Nb S460ML 0.12 1.60 0.04 0.025 0.012 0.02-0.06 0.10 0.06

Table A-3. Material properties for steel, liquid flux, water and substances simulating the liquid flux in the physical model.

Material property Steel Liquid

flux Water Oil Hexane White oil

Temperature [°C] 1522 1460 20 20 20 20 Density [kg/m³] 7020 2600 998 913 814 868 Surface tension [N/m] 1.56 0.054 0.073 0.033 0.0264 0.023 Dynamic viscosity [kg/(ms)] 0.0065 0.6 – 1.2 0.0011 0.0840 0.0053 0.0087 Interfacial tension [N/m] 1.3* 1.3* - 0.018** 0.00176** 0.047** Weber number 661 7704 2187 4427 4933 5019

*steel against liquid flux ** oil against water

Figure A-2. Multi-hole Nozzle used at CAS billet caster.

135

Table A-4. Steel CAS 420A7 160*160mm2 size - Details of ghost line found on the heat 872971.

line slice amount and location of the ghost line max depth [mm] severity distance from the edge [mm]

L1 1A 1 (quadruple), inner side 6-12 medium 15-25 1B - - - - 1C - - - -

L2 2A 1 (double), inner side <4 low 35-45 2B 1, inner side 3-6 low 16 2C 1, inner side <8 high 33

L3 3A 1 (quadruple), inner side 7-13 medium 20-30 3B 1 (triple), outer side 5-10 medium 15-25 3C - - - -

L4

4A 1 (double), inner side 4-9 medium 20-25

4B 1 (triple), inner side 5-10 medium 10-20

1, outer side 6-11 medium 48

4C 1 (triple), outer side <8 high 25-35

1 (double), outer side 5-10 medium 20-22

Table A-5. Steel CAS 420A7 160*160mm2 size - Details of ghost line found on the heat 972463.

line slice amount of ghost line max depth [mm] severity distance from the edge [mm]

L1 1 1 8-11 low 17-22 mm 5 - - - - 9 1 6-11 medium mid-face

L2 2 - - - - 6 1 6-10 low 23-27 mm

10 - - - -

L3 3 - - - - 7 - - - -

11 2 4-12 low 15-21 mm

L4

4 - - - -

8 1 2-8 medium mid-face 1 0-3 low 25 mm

12 1 5-10 medium 16-22 mm

136

Table A-6.- Steel CAS 420A7 160*160mm2 size - Details of ghost line found on the heat 72034.

line slice amount and location of the ghost line max depth [mm] severity distance from the edge [mm]

L1 1 - - - - 5 traces, inner side - - - 9 - - - -

L2 2 traces, inner side - - - 6 1, inner side 7-9 low 19-29

10 1, inner side 9-15 medium 16-21

L3 3 traces, inner side - - - 7 - - - -

11 1, inner side 7-11 low 19-22

L4

4 - - - - 8 1 (triple), inner side 9-11 low 15-20

12 1, outer side 6-10 low 14-19

traces, inner side - - -

Table A-7. Steel CAS 420A7 160*160mm2 size - Details of ghost line found on the heat 72622.

line slice amount and location of the ghost line max depth [mm] severity distance from the edge [mm]

L1

1 1 (double), inner side 5-10 medium 18-20 5 1, inner side 6-9 low 32

9 1 (double), inner side 8-11 low 17-29

diffuse, inner side 5-10 medium 13-17

L2 2 - - - - 6 traces, inner side >10 - 25-35

10 - - - -

L3 3 traces, inner side 8 - 50-55 7 traces, outer side 5-10 medium 27-32

11 - - - -

L4

4 1, inner side 5-8 low 32

traces, inner side 5-10 medium 0

8 traces, inner side 8-12 low 17-29 traces, inner side 5-10 medium 20-26

12 traces, inner side 5-9 low 12-17 traces, outer side >7 - 32-40 traces, inner side >8 - 45-52

137

Table A-8. Steel CAS 420A7 160*160mm2 size - Details of ghost line found on the heat 73012.

line slice location of the ghost line max depth [mm] severity distance from the edge [mm]

L1 1 - - - - 2 - 8-10mm - 21mm 3 - - - -

L2 1 outer side 6-9mm medium 15-20mm 2 inner side/outer side - medium - 3 inner side - high -

L3

1 inner side - high -

2 outer side more than 9mm

high 15-21mm

more than 9mm 15-20mm 3 - 10-13mm - 29mm

L4

1 outer side - high - 2 outer side - medium -

3 outer side 9-13mm

low 19-30mm

more than 8mm 17-21mm

Table A-9. Explanation symbols of IDS model.

Explanation of symbols in IDS model Explanation of symbols in IDS modelF-liq = fraction of liquid Cn = nominal composition (wt%)F-def = fraction of delta ferrite Ci = interdendritic composition (wt%)F-aus = fraction of austenite Ca = dendrite axis composition (wt%)F-euf = fraction of eutectic ferrite F-fer = fraction of delta ferriteF-com = fraction of compounds F-aus = fraction of austeniteH = enthalpy (J/g) F-afe = fraction of ADC ferriteK = thermal conductivity (W/mK) F-ace = fraction of ADC cementiteD = density (kg/m3) F-com = fraction of compoundsLIQ = liquidus temperature (Tliq) H = enthalpy (J/g)fer+ = start of delta ferrite formation K = thermal conductivity (W/mK)aus+ = start of austenite formation D = density (kg/m3)zst = zero-strength temperature (Tzst) Ae3 = Ae3 temperature (equilibrium)fer- = disappearance of delta ferrite endA = end of ADC simulationsSOL = solidus temperature (Tsol)s50 = solidus temperature - 50C QIstr = quality index (0-1) of disturbed strengthening around TzstendI = end of IDS simulations QIsol = quality index (0-1) of reduced ductility around Tsol

QIgra = quality index (0-1) of large austenite grains below TsolQIshe = quality index (0-1) of disturbed shell growth around Tsol

138

Table A-10. Steel CAS 410 – Ghost lines observed on a sample heat, after macro etching (HCl diluted/30min).

line slice depressed site severity

along the inner side

along the outer side at cut begininng at cut end

L1 1 - - medium high 5 - - - high 9 - - - high

L2 2 - medium medium - 6 - - high low

10 low - medium -

L3 3 - - - - 7 - - - low

11 - - - high

L4 4 - low high - 8 low - high high

12 low - high medium

139

Appendix 2 - Deliverables

WP 1

Definition of reference casting conditions

Deliverables Accomplished

Task 1.1 Specification of the casters of the industrial partners being investigated

Definition of operational parameters and set of database for the models

yes

Task 1.2 Summarising known interrelation between casting parameters and product quality as well as process stability

Definition of operational parameters and set of database for the models

yes

WP 2

Simulation of mould powder behaviour

Deliverables

Task 2.1 Thermal transient model of powder heating and melting

Model able to calculate thi ckness of liquid, sintered and powder layer

yes

Task 2.2 Two-phase fluid-dynamics model of the steel/slag system

Model able to calculate distribution of liquid pool thickness and velocity field along the perimeter

yes

Task 2.3 Fluid dynamics model of the flux infiltration

Model for casting powder

yes

Task 2.4 Supplementing physical model trials for the casters

Flow information for adjustment and validation

yes

Task 2.5 Adaptation of DUNAFERR model for the qualification of the liquid pool depth and its shape

Model for the calculation of the liquid pool depth and its shape

yes

WP 3

Simulation of solidification behaviour Deliverables

Task 3.1 Steady-state 3D thermo-mechanical model of the mould

Model able to calculate temperature thermal field and distortion of mould

yes

Task 3.2 Transient 2D thermo-mechanical model of the solidification of steel in the mould

Model able to calculate temperature and strain distribution in the solidifying shell

yes

Task 3.3 Development of steady-state 3D thermo-fluid-dynamics model of the strand

Model able to calculate temperature and fluid flow in the strand

yes

Task 3.4 Adaptation and further development of the macrosegregation model

Model able to predict macrosegregation behaviour

yes

Task 3.5 Adaptation and further development of the columnar to equiaxed transition model

Model able to predict transition behaviour

yes

Task 3.6 Solidification model Model able to calculate the solidification phenomena

yes, but change of plan to

other solidification model

Task 3.7 Adaptation of the DUNAFERR model for predicting temperature evolution and surface and inner crack formation

Model able to predict defect formation on the basis of temperature evolution

yes

140

WP 4

Simulation of phase transformation Deliverables

Task 4.1 3D heat transfer and phase transformation model

Model able to calculate phase transformation all along the strand

yes

WP 5

Model application and validation Deliverables

Task 5.1 Adaptation of caster moulds Thermocouple equipment (CAS, DUNAFERR), inspection system (DUFERCO)

yes Unlike planned thermocouples inserted also to

DUNAFERR caster Task 5.2 Cast trials, data acquisition and

sample collection for microstructural analysis

Data of in-mould temperature, operating parameters, mould heat flux, samples from as cast products, relative to one cast trial

yes

Task 5.3 Microstructural analyses Measure of chill zone thickness, SDAS, central equiaxed zone size

yes

Task 5.4 Calibration of the models Numerical results for one cast trial condition using all models

yes

Task 5.5 Definition of critical variables Definition of safety ranges

Selection of variables describing critical events Safety ranges for critical variables

yes

Task 5.6 Calculation of the performed trials Results of calculations for all trials

yes

WP 6

Development and application of the empiric on-line model for process control

Deliverables

Task 6.1 Formulation of empirical relationships between the critical variables and input parameters

Results in terms of critical variables versus input parameters in an ordered database

yes

Task 6.2 Estimation of the limits for the variable changes inside which a regular casting process is guaranteed.

Relationships to relate critical variables to safe ranges of casting parameters

yes

Task 6.3 Elaboration of guidelines for the extension of the new on-line model

Guidelines for the extension of the new on-line model

yes

WP 7

Project coordination and reporting

Task 7.1 Co-ordination

yes

Task 7.2 Exchange meetings

yes

Task 7.3 Reporting

Reports yes

141

Appendix 3 - Critical parameters and safety ranges CSM and CAS

o Critical parameters surface velocity cv

heat flux difference between the mid-face and the corner, Q∆ o Safety ranges

cv less than 0.30-0.35m/s

Q∆ less than 0.30MW/m2 o Empirical relationship between critical variables, objective of WP6:

( )( ) ( )nm

c

kT

BIvgapmouldtobarQ sol

α∝−−∝∆

where:

solTα is the steel linear thermal expansion coefficient at the solidus temperature

BI is the casting powder basicity index k , m and n are coefficients

BFI

Critical parameters Safety ranges

Minimum Liquid flux thickness 8 - 10 mm

Maximum Surface velocity 0.2 – 0.4 m/s

Maximum Surface wave height 15 – 20 mm

AALTO In terms of defining critical parameters in continuous casting seven mathematical quality indices were introduced by AALTO for steels with the data from IDS solidification model. These indices predict as-cast steel quality. (0= excellent quality, 1= poor quality). Solidification related quality indices QISTR=strengthening problems in mushy zone

⋅

∆−−= 3.02 )()3(20.0exp1

dtdT

dTdf

TQISTR

γ

where ∆T=abs(TZST-TAUS+) is a p ositive temperature difference between the zero s trength temperature (TZST) and austenite start temperature (TAUS+) (IDS output), dƒγ/dT is the growth of austenite fraction as a function of temperature (IDS output) and dT/dt is a cooling rate (°C/s). QISOL=ductility drop close to solidus temperature

+∆−−= 3.05.0 ))(31(05.0exp1

dtdTfTQISOL

γ

142

where ∆T=T2%L-TSOL is the temperature difference in the end of solidification, when the liquid fraction drops from 2% to 0.5% (IDS output, fraction 0.5% equals to TSOL), ƒγ is the austenite fraction at solidus temperature (IDS output) and dT/dt is the cooling rate (°C/s)

⋅

∆−−= 3.02 )()3(5exp1

dtdT

dTdf

TQISHE

γ

where ∆T=abs(TSOL-TAUS+) i s t he p ositive t emperature d ifference b etween t he s olidus t emperature (TSOL) and austenite formation temperature (TAUS+) (IDS-output), dƒγ/dT is the austenite phase growth in t erms o f t emperature ( IDS-output), d T/dt is t he lo cal c ooling r ate ( °C/s) o f the s trand from h eat transfer models. QIGRA=ductility drop induced by large grain size

−−= 3)

3300(exp1

γDQIGRA

where

)80

exp(1044.3)/exp(1

)/exp(1836.01841.0 9γ

γ TdtdT

dtdTD −⋅++

−=

is the calculated grain size (µm) (IDS model). In Eq. (6) Tγ is the highest temperature (°C), where the structure can be fully austenitic. (Figure 33) (IDS output) and dT/dt is the cooling rate (°C/s). Austenite decomposition related quality indices QICOM=ductility drop induced by increased precipitation growth

[ ]∑∑ −−−= )(100exp1 1200C

CC

COM ffQI where ΣƒC is a sum of mole fraction of all the precipitations in temperature T and ΣƒC

1200C and is the corresponding mole f raction in 1200°C (both t erms a re calculated with IDS model us ing the cooling rate obtained from the heat transfer models. QIADC=ductility drop in start of austenite decomposition

[ ]ADCADC fQI 30exp1 −−= ƒADC<0.1

[ ]3)/(003.0exp1 ADCADC fQI −−= ƒADC>0.1

where ƒADC is a fraction of decomposed austenite in temperature T (is calculated with IDS model using the cooling rate calculated with heat transfer models.. QIHAR=hard final structure

MARBAIbaiFER HV)(HV)(HV)(HV marCpcpeap ffffffff +++++++= αγα

where terms ƒα, ƒγ, ƒpα and ƒpea represent fractions of soft ferritic phase fractions (α=ferrite, γ=austenite, pα=proeutectoid ferrite, pea=pearlite), terms ƒbai, ƒpc and ƒC represent fractions of medium hard phases in s tructure ( bai=bainite, p c=proeutectoid cem entite, C =precipitations) an d t erm ƒmar describes a fraction of the hardness phase, martensite, in structure. (The artificial classification of austenite into the soft phases as well as proeutectoid cementite and precipitations into the medium hard phases does not produce a big error as their portions in room temperature are small.)

143

All phases in Equation can be calculated with IDS model. British Steel Corporation has presented the following equations to the terms HVFER, HVBAI and HVMAR HVFER = 42+223CC+53CSi+30CMn+7CCr+19CMo+12.6CNi+(10-19CSi+8CCr+4CNi)⋅log(dT/dt) HVBAI = -323+185CC+330CSi+153CMn+144CCr+191CMo+65CNi+ (89+53CC-55CSi-22CMn-20CCr-33CMo-10CNi)⋅log(dT/dt) HVMAR = 127+949CC+27CSi+11CMn+16CCr+8CNi+21⋅log(dT/dt) where C i is a wei ght percent [wt%] of a co mponent and dT/dt is an average predominant cooling rate during austenite decomposition [oC/hour] (TEMPSIMU-output). The equations (10)-(12) a re valid for the compositions up to 0.7wt%C, 0.6wt%Si, 1.6wt%Mn, 0.5wt%Mo and 9.9wt%Ni. If hardness is not a desired p roperty, f or ex ample b ecause of r eheating i nduced cr acking, can t he dr op i n ductility be represented as

1000/HVQIHAR = For cal culating t hese i ndices f or s teel composition t he r equired d ata ar e o btained f rom IDS m odel (includes ADC module). DUFERCO

o Copper equivalent

SNiSnCuCueq %2%%10% ×−−×+=

o Ferrite potential

For carbon and low alloy steels: ( )pp CF −×= 5,05,2

Where v alues o f Fp>1 ar e i ndicative o f a f ully ferritic s tructure ab ove a nd below t he s olidus temperature. Pure δ iron has a value of 1.25 and other alloys with ferrite stabilizers such as Cr and Si have values higher than 1 ( e.g. s ilicon s teels and 430 s tainless grades). Values of <0 indicate a f ully austenitic structure. The carbon equivalent is calculated:

STiMoCrSiNNiMnCCp %7.0%24.0%1.0%04.0%14.0%7.0%1.0%04.0% −−−−−+++=

144

• Surface level quality index determined from the melt level variation in the mould

DUNAFERR and OBUDA

o Porosity level in the centre part of slab

o Relative flow rate of mushy liquid in the centreline of slab

Critical parameter P [mm2], Porosity level in the centre part of slabs

Defects controlled porosity, centreline segregation, centreline discontinuity in the slab and as a result discontinuity in the centreline of hot rolled strips and plates

Remark: centreline segregation is caused partly by porosity and partly by macrosegregation in the centre part of slab

Safety range On the basis of theoretical considerations which are in relative good accordance with the available experiences concerning the DUNAFERR casting machine

P =< 6: small risk of porosity, it can be eliminated by hot rolling

P > 6: high risk of porosity, generally cannot be eliminated by hot rolling

Remark: the elimination of centreline porosity highly depends on the thickness of rolled product

1. DEFINITION: • Arbitrary index to assess the surface quality of billets

2. SAMPLING: • - For each billet (start and finish is defined by the cutting time) • - Signal level variation (from start to finish the level variations induced by

cutting are not measured) • - Each ½ second

3. ARBITRARY INDEX 4. THRESHOLDS:

• INDEX 0 when 99 % the variation of level ≤ 3%; • INDEX 1 when ≥ 1 % the variation of level >3%; • INDEX 2 when ≥ 1 % the variation of level > 5%; • INDEX 3 when ≥ 1 % the variation of level > 10 %;

145

Critical parameter F [mm/mm], Relative flow rate of mushy liquid at the liquid/mushy boundary in the centreline of slab

Defects controlled macrosegregation, centreline segregation, macrosegregated centreline area of slab and as a result centreline segregation in the hot rolled strips and plates (in general higher carbon,

manganese and sulphur content in the centre part than the nominal values)

Safety range On the basis of theoretical considerations which are in relative good accordance with the available experiences concerning the DUNAFERR casting machine

0 < F < 0.001: small risk of centreline macrosegregation, the macrosegregated mushy liquid is a little bit squeezed out from the mushy area, the mushy liquid moves in the direction of the meniscus inside the slab.

F < 0: high risk of centreline macrosegregation, the macrosegregated mushy liquid is sucked into the mushy area, the mushy liquid moves in the direction of casting inside the slab.

F > 0.001: higher risk of centreline macrosegregation, the macrosegregated mushy liquid is drastically squeezed out from the mushy area.

146

Appendix 4 - General description of the Liquid Motion Intensity (LMI) model by OBUDA and DUNAFERR This model aims at a realistic characterization of the movement of liquid (direction and level) inside the slab d ue to s olidification p rocesses (shrinkage) a nd due t o t he t ypical de formation c onstrains (supporting roll positions, eccentricity, bulging) of continuously cast slabs, which can affect the balance of the solid and of the liquid inside the product. The two dimensional model describes the processes in longitudinal c ross sections of s labs perpendicular to the wide s ide. For the sake of s implicity, in th is model the liquid movement is analysed in a planar approach but it is evident that the real problem has a three dimensional characteristics. Because of symmetries, the analysis of the half cross-sectional area is sufficient (see Fig. 1). Let us define the parameters of shell thickness. The heat transfer models provide thickness values of the solid a nd s emi-solid ( solid + m ushy) s hell, w hich belong to th e liq uidus a nd s olidus te mperatures according to Fig. 1. In order to simplify the situation in the mushy, let us divide the mushy zone thickness into two virtual layers which represent the virtual thickness of solid and the virtual thickness of liquid, respectively. The solid/liquid ratio of the mushy zone can be calculated by commercial software for cooling rates close to the e quilibrium. Let u s d istribute th e t otal le ngth o f th e s trand in to s lice e lements w ith th e s ame thickness. T he di stance o f a s lice f rom t he m eniscus l evel i s given b y t he h(i) function, wh ere i = 0,1,2,... w. For the total half thickness of the strand in slice i, the following equation can be written:

iliq

imush

isol

itot dddd ++= , where (Eq. 1)

iliqmush

isolmush

imush ddd ,, += , (Eq. 2)

where wi ≤≤0 is fulfilled. The d values in Eq. 1 a nd 2 can be corrected b y the shrinkage of shell according t o act ual t emperature d istribution o f t he s lice an d co nsequently f or t he co rrected s lab thickness we obtain

icorrliq

icorrliqmush

icorrsolmush

icorrsol

icorrtot ddddd ,,,,,,, +++= (Eq. 3)

Figure 1. Cross-section of slab under investigation.

If th ere is n ot a ny e ffect w hich c ould m odify the a mount of liq uid o r s olid, in the slice u nder

dsol dliq

dmush

sliq

dtot

Sim

met

rypl

ane

Surfa

ceof

slab

Dendritic trunks(mushy solid)

Liquid between dendrites(mushy liquid)

Solidshell

Liquid

Mushy

Tsurf Tsol

Tliq

Tcentr

147

investigation the sum of the total amount of solid will be

icorrsolmush

icorrsol

icorrtotsol ddd ,,,,, += (Eq. 4)

and the total amount of liquid will be

icorrliqmush

icorrliq

icorrtotliq ddd ,,,,, += . (Eq. 5)

The n ext s tep i s t he cal culation o f g ap wh ich i s av ailable f or t he s lab at a g iven d istance f rom t he meniscus level. Let us introduce rnom nominal half gap size parameter, which can be calculated from the setting data of the supporting rolls as a function of h(i) distance from the meniscus level as follows:

))(( ihfr nomi

nom = (Eq. 6) The fnom function can b e i nterpreted al ong t he wh ole l ength o f t he s trand, t he g ap v alues can b e calculated also between successive rolls, i.e. this function describes the outer contour line of the strand when only the nominal roll setting data are taken into account. This outer contour line under industrial circumstances can be modified by different factors, and the differences can also be given as a function of the distance from the meniscus level:

))(( ihfr posipos =∆ (Eq. 7)

represents the setting errors, real settings and wear of rolls,

))(( ihfr ecci

ecc =∆ (Eq. 8) contains the effect of eccentricities of rolls,

))((lglg ihfr bui

bu =∆ (Eq. 9) describes the bulging effect. In summary, under industrial circumstances the outer contour line of the available room for the strand at a given h(i) distance from the meniscus can be estimated by the following expression:

ibu

iecc

ipos

inom

i rrrrr lg∆+∆+∆+= . (Eq. 10) Inside the s trand the l iquid movement depends on the difference between ir and i

corrtotd , . The ir = i

corrtotd , means t hat t he s hrinkage o f t he s hell i s p erfectly c ompensated b y outer constrains. In ir > i

corrtotd , case more room is available for the strand than necessary, so some extra liquid will be sucked

in for compensation of the extra volume. If ir < icorrtotd , is valid, the squeezing out of liquid will take

place. Let us investigate the h istory of one s lice f rom the point of v iew of l iquid amount balance. For each position of the slice the difference is

itermtot

ii drd ,−=∆ (Eq. 11) To determine the amount of sucked in or squeezed out liquid, let us define the following expression:

148

iii ddp ∆−∆=∆ −1 (Eq. 12)

In o rder t o t ake i nto acc ount t he ef ficiency of ch ange o f volume (i.e. t he co nnection b etween t he deformation of t he s hell a nd t he v olume c hange i nside t he s lab), t he i ntroduction o f a correcting parameter is necessary:

iicorr pCp ∆⋅=∆ 3 , (Eq. 13)

where C3 constant parameter is lower than 1. It follows from the above mentioned considerations that the thickness of liquid layer in the i-th slice is:

iccrr

icorrliqmush

icorrliq

icorr

iliq

icorrliq pddpdd ∆++==∆+= ,,,, (Eq. 14)

Calculation of porosity parameter

Because o f the two-dimensional analysis, the icorrp∆ value can be interpreted as the t hickness of the

extra liq uid ( can b e p ositive o r n egative) in th e s lice u nder in vestigation. Let u s in troduce iV∆parameter, which characterizes the volume change in the planar approach when the s lice moves f rom the i-1 position to the i position.

))1()(( −−⋅∆=∆ ihihpV icorr

i /2 (Eq. 15) The LMI parameters can be generated by cumulation of iV∆ over specified regions of strand and under different cumulation rules. As an example, the in troduction of LMI1 parameter i s demonstrated here. Let z be the serial number of the first slice in which the liquid amount of the mushy is zero. In this case h(z) gives the pool depth in the strand calculated for the solidus temperature. In order to characterize the liquid movement inside the strand, the LMI1 parameter can be written in a general form:

∑=

∆=z

i

iVLMI1

1 . (Eq. 16)

Only for sucking in of the liquid

∑=

∆=z

i

iin VLMI

11 ( iV∆ <0), (Eq. 17)

and only for squeezing out of the liquid

∑=

∆=z

i

iout VLMI

11 , ( iV∆ >0) (Eq. 18)

From t he v iewpoint o f c entreline s egregation, t he m ovement o f t he l iquid i n t he m ushy a rea of t he strand (i.e. that part of the strand which is between the pool depth calculated for the liquidus and for the solidus) has a s pecial importance. Let us define the pool depth calculated for the liquidus at h(f), and another s lice wi th s erial n umber g between h(f) and h(z) which co ntains a g iven r atio of mushy liquid/mushy solid. For the last stage of solidification between h(g) and h(z), the LMI7 parameter can be defined as follows:

∑=

∆=z

gi

iVLMI7 , ( iV∆ <0). (Eq. 19)

A set of calculation was performed in the frame of the extended statistical analysis [1,2] including also the LMI7 parameter. The most important conclusion of this work w as that the c orrelation c oefficient between the calculated and measured centreline segregation numbers depends on the position of slice g (i.e. on the mushy liquid/mushy solid ratio), and the best correlation belongs to about 30 % of liquid. Because of the physical meaning of Eq. 18, the LMI7 can be considered as the final porosity level of the center area of the strand. The porosity function which describes the development of centreline porosity

149

in the strand can be written as follows:

∑=

∆=n

gi

iVnLMI )(7 ( iV∆ <0) (Eq. 20)

where g ≤ n ≤ z is valid.

Calculation of flow rate parameter

The flow rate parameter, which is introduced in this approach is used for steady state casting conditions, when t he cas ting r ate i s co nstant. Let us d efine L as t he l ength o f t hat p art o f t he s lab, wh ere t he movement of mushy liquid is expected:

L = h(g) - h(f) (Eq. 21) After dividing this distance into n slices, let us define Li as the distance from the meniscus level to that border of the n-th slice which is closer to the end of the casting machine. The n-th slice has two borders, one of them is at Ln-1 position, the other is at Ln. Through the cross section at Ln distance there is no liquid movement, because Ln = h(g). On the other side of this slice (at Ln-1 position) the liquid thickness can be given according to Eq. 14 as follows:

11,,

1,

111,

−−−−−− ∆++==∆+= ncorr

ncorrliqmush

ncorrliq

ncorr

nliq

ncorrliq pddpdd . (Eq. 22)

The liquid movement intensity (I) by definition is the quotient of the extra liquid inside the slice and the thickness of liquid layer at that border of the slice which is closer to the meniscus. For the n-th slice the border at Ln-1 position is closer to the meniscus and the extra liquid can move only through this border. The liquid movement intensity at this border can be defined as

In-1 = 1,/ −∆ ncorrliq

ncorr dp (Eq. 23)

In t he t wo-dimensional an alysis p arameter g iven b y Eq. 2 3 can b e considered as a l iquid movement intensity p arameter wi th a u nit o f m m/mm, wh ich ch aracterizes t he r ate o f r elative f luid f low. The liquid movement developed at Ln-1 position affects the liquid movement in all cross sections between Ln-1 and t he m eniscus l evel. A t Ln-2 position th e a vailable c ross s ection ( thickness in 2 D) f or th e movement o f the liquid is 2

,−n

corrliqd , and through this the extra l iquid in both the n-th and the n-1-th slices can move, so the intensity at this position will be

In-2 = In-12,

1, / −−⋅ n

corrliqn

corrliq dd + 2,

1 / −−∆ ncorrliq

ncorr dp (Eq. 24)

By continuing this logic, for an arbitrary i-th slice one can calculate the intensity as follows:

Ii-1 = Ii1,, / −⋅ icorrliq

icorrliq dd + 1

,/ −∆ icorrliq

icorr dp (Eq. 25)

where i = n, n-1, n-2…1. In i=1 case the equation

I0 = I10

,1

, / corrliqcorrliq dd⋅ + 0,

1 / corrliqcorr dp∆ (Eq. 26) gives th e liq uid m otion in tensity p arameter o nly a t th e b eginning o f th e mushy section, i. e. a t h(f) position of the strand.

Summary

The h eat tr ansfer m odel c ompleted b y th e L MI m odule g ives a p otential o pportunity to ta ke in to account a ll i mportant e ffects w hich pl ay role dur ing s lab c ontinuous c asting unde r i ndustrial

150

circumstances. T he r esults o f m odel a pplication in o ptimization o f in dustrial c asting te chnology [3] proved the reliability of the developed calculation method.

References

[1] M. Reger, H. Kytönen, B. Verő, A. Szelig: Estimation and Consequences of Shrinkage of Steel Slabs, MATERIALS SCIENCE FORUM, Vol 589, pp. 43-48, 2008 [2] M. Reger, H. Kytönen, B. Verő, A. Szelig: On the Centreline Segregation of CC Slabs, 6th European C ontinuous C asting C onference, 3 -6 J une, R iccione, I taly, 2 008, A ssociazione i taliana d i metallurgia, pp. CD1-12 [3] Reger M, Vero B, Csepeli Zs, Jozsa R: Prediction of Centreline Segregation of CC Slabs, In: 7th European Continuous Casting Conference, Düsseldorf, Germany,: CD pp. x1-x9.

Abbreviation of symbols

Symbol Description Unit Symbol Description Unit

C3 constant - h(f) pool depth belonging liquidus mm

dsol solid shell thickness mm h(g) pool de pth be longing 30 % mushy liquid mm

dmush mushy thickness mm h(z) pool depth belonging solidus mm

dliq liquid thickness mm LMI(1-7) Liquid M otion Intensity parameters mm2

dmush,sol mushy solid thickness mm rnom half gap mm

dmush,liq mushy liquid thickness mm r half thickness of strand mm

dsol, corr corrected solid shell thickness* mm sliq shell th ickness b elonging to liquidus mm

dliq, corr corrected l iquid l ayer thickness* mm Tsurf surface temperature oC

dsol, tot, corr corrected solid thickness* mm Tsol solidus oC

dliq, tot, corr corrected liquid thickness* mm Tliq liquidus oC

dtot half thickness of strand mm Δp liquid thickness difference mm

dtot, corr corrected half width* mm Δpcorr corr. liq uid th ickness difference* mm

dmush, liq,corr corr. mushy liquid thickness* mm Δrpos gap d ifference cau sed b y positioning error mm

dmush, sol, corr corr. mushy solid thickness* mm Δrecc gap d ifference cau sed b y eccentricity mm

fnom(h) outer c ontour function o f the slab defined by rolls Δrbulg gap d ifference cau sed b y

bulging mm

fpos(h) roll positioning error function ΔV liquid amount difference in 2D mm2

151

fexc(h) eccentricity error function I flow rate intensity parameter mm/

mm

fbulg(h) bulging error function L length o f th at p art o f th e s lab, where m ushy l iquid m ovement takes place

mm

h distance from meniscus mm Li distance from meniscus mm

h(w) length of casting machine mm

* corrected by the solidification and thermal shrinkage

European Commission EUR 25094 — Integrated models for defect free casting (DEFFREE) Luxembourg: Publications Office of the European Union 2013 — 151 pp. — 21 × 29.7 cm ISBN 978-92-79-29038-1doi:10.2777/57068

EUROPEAN COMMISSION Directorate-General for Research and Innovation Directorate G — Industrial Technologies Unit G.5 — Research Fund for Coal and Steel

E-mail: rtd-steel-coal@ec.europa.eu RTD-PUBLICATIONS@ec.europa.eu

Contact: RFCS Publications

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Integrated modelsfor defect free casting

(Deffree)

doi:10.2777/57608

Integrated models for defect free casting (D

effree)EU

EUR 25874

KI-NA-25874-EN

-N

The objective of the project was to develop a new modelling-based optimisation and quality control system for continuous casting. The concept was based on studying critical parameters affecting steel quality and finding safety ranges for them to ensure good quality in continuous casting.

Several fundamental and semi-empirical models were developed in the project. The critical features affecting steel quality were defined through mathematical modelling and industrial casting trials. Both good quality casts and casts with some defects were simulated to find features which have an effect on steel quality. Cracking indices, fluid flow parameters in the mould and segregation severity parameters are examples of critical parameters defined in the project. Safety ranges inside which the critical parameters had to stay during casting were determined in steady-state casting conditions. If a critical feature could not be adjusted on-line during casting, for example, surface velocity of liquid in the mould, this feature was expressed as a function of casting parameter, e.g. casting speed, which can be controlled and modified during casting.

For optimising and controlling steel quality during casting the following online models were developed in the project: transient 2D centreline segregation model, dynamic 3D heat transfer model and inverse mould heat flux difference model. These models can be applied also to other casters for online simulation, once the caster has been set up and casting process data is available.

Studies and reports

Research and Innovation EUR 25874 EN