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Control the process to control the Product Based on a 30-year experience, SC-Consultants is your partner in manufacturing processes optimization by providing numerical engineering applied solutions SC-Consultants

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Page 1: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

Control the process to control the Product

Based on a 30-year experience, SC-Consultants is your partner in manufacturing processes

optimization by providing numerical engineering applied solutions

SC-Consultants

Page 2: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

2

The SC-Consultants company

30 years of experience in consulting actions and software solutions provider for manufacturing processes :

Foundry, Casting, Heating & Cooling, SolidificationAeronautic / Automotive / Nuclear / Hydraulic

ExtrusionAgro & Pet Food / Plasturgy

Mixingadvanced materials, Pharma

Page 3: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

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The SC-Consultants company

A French company

Based in Saint Etienne (France) and a subsidiary in Montreal (Canada)

Specialized in the industrial processes optimization

Software edition

Services and consulting

10 employees

Worldwide experience and implementationR&D facilitiesTechnical partnershipsCommercial partnerships

Page 4: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

Headquarters

offices

representatives

customers

SC-Consultants network

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1

The SC-Consultants company

StrategicInitiatives

Services

Software

Strategic InitiativesScientific community

For project development

For collaborative R&D

ServicesDissemination of R&D outcomes

Consultancy

Technical assistance on process simulation

Training

Software solution providerProcess specific software EditionApplication specific software Development

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R&D participation

Partnerships with specialized laboratories

CEMEF From Mines ParisTech

Material behaviour, numerical developments

INRA

National Research Center on Agro Food

Material characterization

Institut Jean Lamour

From Ecole des Mines de Nancy

Metalworking industries

Techno partners

Aimplas, Fraunhofer, Univ Bonn, Univ Cleveland, Univ Lowell, ...

The SC-Consultants R&D background

Page 7: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

Control the process to control the Product

Based on a 2D model, the Solid software is dedicated to casting/ingots casting simulation

Solid® software

Page 8: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

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Introduction

ApplicationsFor simplified geometries (2D)Continuous castingIngots castingFixed mesh (no distorsions)

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Collaborative model

Scientific background Research development performed in close collaboration of Pr Herve Combeau from IJL – Nancy Lorraine University

List of publication available

Continuous development since 1993Industrial consortium (national and private funds)

Software Research industrialization performed by SCCSolid Users's Club

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Overview

Simulation software for solidification

Features

Benefits

For all Casting issues

2D Model

For any applications Fast

computationsIndeep analysis

Process Control Knowledge capitalization

Easy set upFast computation Fast ROI

Screening functioning window

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Solid focus

Solid : simulation of metallic alloys solidification

Liquid Solid

Phase change

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State diagram

Eutectic + α

α

L + α

L

Temperature decrease

At the equilibrium state

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The solid state – Typical structure

Composed by a set of "grains"

Structure example

Columnars

Equiaxes

Dendritic Equiaxes

Solidification local time, shrinkage, porosity, grains morphology

Industrial scale segregations (macro, meso and micro)

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Macroscopic view thermo solute convection

Thermal convection Solute convection

Case of a lighter solute as the environment liquid

Case of heavier solute as the environment liquid

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Microscopic – Simplified model for solidification

Simplified growth : Perfect diffusion

No diffusion

Xs Xl

Xs

Xl

solid liquid

x

k = Xs / Xl

Xs Xl

solid liquid

Xs*

Xs*

Xl

x

k = Xs / Xl

Xs

X l=X 0

f l+(1−f l )k

X l=X 0⋅f lk−1

Page 16: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

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The different phenomena in solidification

Thermal

CFD

Segregation+

Growth

Process parameters and alloys

Thermo-Solute convection+

Solid motion

Grains growth+

Microsegregation

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Solid - 4 levels of modelingThermal

Solidification front , Temperature

Thermal + Fluid Mechanics + segregations (weak coupling) – No solid motion

Solidification front, Temperature

Velocity, pressure

Local compositions

Thermal + Fluid Mechanics + segregations (strong coupling) – No solid motion

Solidification front, Temperature, velocity, pressure

Local composition

Thermal + Fluid Mechanics + segregations (strong coupling) + solid motion + ECT (in option)

Solidification front, temperature, velocity, pressure

Local composition

Structures

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Computations

2D resolution

Finite volume

Fluid mechanics : simplex method

Growth : from simple to sophisticated scheme (dendritic, ….)

Page 19: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

In Practice - 1

ConfigurationGeometry definitionSetting of the appropriate materials and BC (RDB)Setting of the mesh (FV)

Data file construction by modulesFiles (non homogeneous initialisation, filling, ...)Computation options, model selectionThermo-physical and metallurgical properties of the alloy Thermo-physical properties of the molding elementsQuantification of boundary conditions

Computation setting upAccording to the model level : tens of minutes to ….

Results analysisIsovalues maps, curves, … with Paraview software

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In Practice - 2 Configuration and data file: an integrated framework on windows system

Solver : on demand on windows or Linux system /Paraview for post-process

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Configuration : geometry, materials and BC

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Configuration : mesh definition

Zoom

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Control file construction: integrated

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Control file construction: integrated

Visualization of solidification path

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Taking into account filling: a simplified approach

Ref : 3t3 ingot – Aubert & Duval

Initialization with an empty mold At the end of the filling

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Taking into account filling: a simplified approach with a list of available results

Localization of secondary shrinkage and map of C segregations

Ref : 3t3 ingot – Aubert & Duval

Localization of primary shrinkage and Niyama criterium

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Taking into account filling: a global analysis Zoom on the filling stage

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.140

20

40

60

80

100

Evolution of volumes

%vol_remp%vol_s

Time(h)

Volu

me

(%)

Ref : 3t3 ingot – Aubert & Duval

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14

-2.50E+05

-2.00E+05

-1.50E+05

-1.00E+05

-5.00E+04

0.00E+00

Evolution of thermal flux

Filling

time (h)

flux

(W

/m2.

°C)

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Initialization with heterogeneous data: continuous simulation with unmoulding option

Instantaneous unmoulding

12 12.2 12.4 12.6 12.8 13 13.2 13.4 13.6 13.8 14

-3.00E+03

-2.50E+03

-2.00E+03

-1.50E+03

-1.00E+03

-5.00E+02

0.00E+00

Evolution of thermal flux (alloy)

SolidificationAfter unmolding

time (h)

flux

(W

/m2)

End of moulding stage (13h)

Thermal simulation(30mn)

Ref : 3t3 ingot – Aubert & Duval

Page 29: SC-Consultants€¦ · advanced materials, Pharma. 3 The SC-Consultants company ... Industrial consortium (national and private funds) Software Research industrialization performed

2929

Applications ofSolid® software

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Simulation application: Prediction in a 65 ton steel ingot (ArcelorMittal Industeel, France)

Macrosegregation prediction in a 65 ton steel ingot – Combeau et all – ICRF, 201230

Development of macrosegregation and macrostructure

Solid-liquid interaction Sedimentation and packing

Grain growth Morphology development

Nucleation and fragmentation => CET

Flow through the columnar zone

++

--C

t

rv

l T

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Industrial conditions - 65 ton ingot (ArcelorMittal Industeel, Le Creusot)

C 0.22%

S 0.007%

P 0.008%

Si 0.18%

Mn 0.25%

Ni 1.14%

Cr 1.6%

Mo 0.19%

Thermosensors measurementsin the mold

Sulfur print Macrostructure & macrosegregation

Exotermic powder

Cast iron molds

Cast iron plate

Hot top

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Simulation conditions in Solid - 65 ton ingot

0 2 4 6 8 10 12 14 160

100

200

300

400

500

600

700Temperature evolution over time

T14 ExpT14 SimT22 ExpT22 Sim

time(h)

tem

pera

ture

( °

C)

22

14

h a =

(7.5

+4×

5.67

×10

-8 ε

T3 )

W/m

2/K

ε =

0.9

, T

ext =

20

°C

Boundary conditions validated according to measurements in the mold

Exothermic powder

perf

ect c

onta

ct

Comparison between 2 levels of modeling : fixed solid and grain motion

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Global analysis: temperature evolution

Start 4h 8h30

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Global analysis: local solidification time, liq fraction evolution after 8h30

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Macrosegregations predictions - 65 ton ingot

ΔC/C0

Fixed solid Moving grains Centerline segregation

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Macrosegregations predictions - 65 ton ingot (ArcelorMittal Industeel, Le Creusot)

ΔC/C0

Fixed solid Moving grains Centerline segregation

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Macrosegregations predictions - 65 ton ingot (ArcelorMittal Industeel, Le Creusot)

ΔC/C0

Fixed solid Moving grains Centerline segregation

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Understanding the macrosegregations creation - 65 ton ingot – Fixed solid

1h 30min 3h 45min 8h 10min 20h

ΔC/C0

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Understanding the macrosegregations creation - 65 ton ingot – Fixed solid

1h 30min 3h 45min 8h 10min 20h

ΔC/C0

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Understanding the macrosegregations creation - 65 ton ingot – Fixed solid

1h 30min 3h 45min 8h 10min 20h

ΔC/C0

++

––

++

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Understanding the macrosegregations creation - 65 ton ingot – Moving grains

1h 15min 2h 40min 3h 45min 20h

T [ºC] ΔC/C0

Grain density

Grain density [m-3]

ΔC/C0

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Understanding the macrosegregations creation - 65 ton ingot – Moving grains

1h 15min 2h 40min 3h 45min 20h

T [ºC] ΔC/C0

Grain density

Grain density [m-3]

ΔC/C0

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Understanding the macrosegregations creation - 65 ton ingot – Moving grains

1h 15min 2h 40min 3h 45min 20h

T [ºC] ΔC/C0

Grain density

Grain density [m-3]

ΔC/C0

++

––

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Understanding the macrosegregations creation - 65 ton ingot – Moving grains

1h 15min 2h 40min 3h 45min 20h

T [ºC] ΔC/C0

ΔC/C0ΔC/C0

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Comparison with experimental results - 65 t ingot

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Comparison with experimental results - 65 t ingot

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Comparison with experimental results - 65 t ingot

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Origin of equiaxed grains origin ? ECT modeling with Solid

Each structure has its own solid phase, extra- and intra-dendritic liquid phases.

Equiaxed grains are blocked when they enter in a REV with columnar struct. already present

Columnar

Equiaxed

Modelling of Columnar-to-equiaxed and equiaxed-to-columnar transitions in ingots using a multIphase model, Leriche et all, MCWASP 2015

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Application to a 6t2 steel (Asco Industries)Element C Si Cr Mn Ni S P Mo

wt % 1.01 0.23 1.34 0.33 0.11 0.021 0.015 0.03

2,7

m

~ 0,65 m

Co

lum

nar

zo

ne

Eq

uia

xed

z

on

e

Structures distribution

Mixed structures (branched grains) Dendritic morphology

Globular morphology

Cast iron mold

PhD T. Mazet 1995

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6t2 ingot – Pre process with Solid

Adiabatic

Con

vect

ive

+ R

a dia

tive

h eat

tran

sfer

t

Symetry

mold

ingot

refractory

Adiabatic

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6t2 steel ingot – Evolution of Carb and Temp

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6t2 steel ingot – ECT position

SimulationExperiment

Hei

gh

t (m

) Simulation

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Continuous casting application -

Inoculants moving integration

Grains size computation

Thermo-solutal convection

Ingot

Ingot mold

Mold

Water streaming

Solid

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Semi continuous casting Al-Cu

Thermo-metallurgical stationary conditions set up

Temperature distribution Cu segregration Structure distribution

Application Constellium

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Summary: Solid ?

Solid is a simulation software dedicated to casting ingot

Solid offersMulti components alloysMaterial molding differentiationFilling (simplified approach)

Solid predicts Global process resultsCasting defaultsSegregation and structure correlated to final properties

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Sciences Computers Consultants(Headquarters)

10 rue du plateau des GlièresF-42000 Saint Etienne+33 (0)4 77 49 75 80

[email protected]

Sciences Computers Consultants Inc.(Sales office North America)1455 rue Drummond, Suite B

Montréal H3G 1W3+1 514 687 4708

[email protected]

Http://www.scconsultants.comHttp://www.mixingsimulation.technology