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  • Advanced Amine Process SimulationModel Development

    Bill Pennycook, Simon Jackson andIain Martin

  • Advanced Amine Process Simulation Model Development Bill Pennycook, Simon Jackson & Iain Martin Davy Process Technology 20 Eastbourne Terrace London W2 6LE [email protected] www.davyprotech.com

    1 Introduction Fig 1.1 Methylamines Unit Davy Process Technology (DPT) has acquired a range of amine production technologies that have been licensed for many years. Following acquisition, DPT engineers critically reviewed the processes and then updated the technologies using advanced development and design techniques which are similar to ones that have been applied on other DPT licensable technologies. Key to this approach was establishing an accurate simulation model and it became apparent that additional data would be required to augment and confirm the available literature studies.

    This paper describes the development of practical techniques that were used to prepare an accurate multi-component simulation models from first principles with particular emphasis on the process for the production of methylamines. These processes include complex aqueous and organic systems and involve dealing with numerous azeotropes which are truly multi-component, in contrast to a binary split of key components in the presence of other more or less volatile minor components. It soon became apparent that the accurate measurement of vapour liquid equilibrium data was particularly challenging for these highly odorous, volatile and corrosive materials and a wide range of techniques and specific laboratory equipment were necessary to accomplish the target. This practical approach enabled analysis of the results for accuracy and provided confidence in the simulations being undertaken. In turn, it was possible to move the technology forward using these models to more accurately predict the performance and optimise equipment design with associated value creation. DPT now has a comprehensive portfolio of highly cost-effective process technologies for the production of the majority of the industrial amines and these are available for licence. Of particular interest is the production of methylamines since this is the largest volume alkylamine produced and also since it feeds in to a range of derivatives which DPT is also capable of licensing.

    2 Description of DPT Flowsheet Methylamines are produced by reacting ammonia with methanol at an elevated temperature and pressure in the presence of a heterogeneous catalyst. A mixture of three amines is formed, monomethylamine (MMA), dimethylamine (DMA) and trimethylamine (TMA). They are separated and purified by distillation. A simplified set of equilibrium chemical reactions that take place are shown below: CH3OH + NH3

    ?

    CH3NH2 + H2O (MMA)

    CH3OH + CH3NH2

    ?

    (CH3)2NH + H2O (DMA)

    CH3OH + (CH3)2NH ?

    (CH3)3N + H2O (TMA)

  • By-product formation and degradation of the products to light ends is minimised by the use of optimised processing conditions and a state-of-the-art catalyst. By-products include CO, H2 and higher molecular weight organics.

    Figure 2.1: Schematic showing a DPT Methylamines Unit

    Fresh methanol and ammonia are combined with recycled amines and ammonia and then vaporised, superheated and fed to the catalytic methylamines converter. In the converter, ammonia and methanol undergo an exothermic reaction to form mono, di- and tri-methylamines in accordance with the reaction mechanism shown. CO, H2 and higher organics are reaction by-products. The split of MMA, DMA and TMA in the reactor product is close to equilibrium (if the catalyst is of the acidic macro-pore type). The equilibrium split depends on the ratio of nitrogen to carbon in the feed. If DMA is desired in higher-than-equilibrium quantity, then excess MMA and TMA can be recycled. The distillation section consists of four columns. The reactor product is fed to the NH3 Column where ammonia is separated overhead as an azeotrope with TMA and returned to the synthesis section. The bottoms stream consisting of amines and water is fed forward to the Extraction Column where TMA is taken from the overheads and drawn as product of recycled to synthesis. The bottoms, containing predominantly MMA, DMA and water, are fed to the Dehydration Column. MMA/DMA is taken overhead and produced water is taken from the bottom stream. The mixture of MMA and DMA from the Dehydration Column is fed to the Product Column, where pure MMA and DMA are taken as products. Ammonia and amine containing vent gases are fed to the scrubbing system so that ammonia and amine are recovered by recycling of the scrubber purge back to distillation. These processes include complex aqueous and organic systems and several azeotropes. They are truly multi-component, in contrast to a binary split of key components in the presence of other more or less volatile minor components.

    3 Introduction to the problem of methylamines distillation modelling The first step in any development is to be very clear about the reasons why this work is being done. So why did DPT need to go back to basics for such a well established process? The distillation scheme had not changed significantly for many years so it was

    necessary to review how to add value. Published data on physical properties for the various mixtures of components in the

    process were neither consistent nor comprehensive. The original design was derived by a combination of basic theory and operational

    experience but had not been accurately modelled using modern computer simulation programmes.

  • DPT needed to be able to simulate the methylamines distillation accurately in order to reduce design margins to a minimum.

    In other processes DPT has proven that sound process modelling enables designers to make considerable cost savings on capital and operating costs. To omit methylamines would have been a departure from normal business practice.

    It was soon realised that this was a difficult task. Methylamines distillation, particularly where water is present is a very difficult system to model . To model properly with high accuracy over a wide range requires a complex model with many interaction coefficients. It was found that commercially available regression packages do not have adequate capabilities (without excessive user programming) to rigorously model the methylamines system correctly. However, this paper describes how commonly available thermodynamic options were used to model plant design and optimisation with appropriate accuracy. Publicly available information was collected and regressed. There was no data for some systems and for others there was only azeotropic data. It became obvious that in-house generation of a considerable amount of VLE data was required. Tables 3.1 to 3.5 show the published data covering azeotropes in a methylamines distillation system. Table 3.1 DMA-TMA Azeotropic data Pressure Boiling

    Point Mol Fraction

    Bara C TMA DMA

    Reference

    1.01 3.0 0.68 0.32 8.39 73 0.23 0.77

    Rohm and Hass Co. (1949)

    26.52 Non-azeotrope Babcock (1936) Table 3.2 MMA-TMA Azeotropic data Pressure Boiling

    Point Mol Fraction

    Bara C TMA MMA

    Reference

    1.01 -5 0.18 0.82 Andrews and Spence (1938)

    5.15 36 0.08 0.92 15.49 75 0.06 0.94 26.52 Non-azeotrope

    Rohm and Hass Co. (1949)

    1.39 0 0.20 0.80 Hacker, Lucus and Gelbin (1964)

    Table 3.3 NH3-TMA Azeotropic data Pressure Boiling

    Point Mol Fraction

    Bara C NH3 TMA

    Reference

    20.27 50 0.914 0.086 Issoire (1961) 40.53 80 0.919 0.081 Issoire (1961) 1.01 -34 0.888 0.112 Issoire (1961) 0.932 -37 0.887 0.113 Issoire (1961) 0.750 -40 0.879 0.879 Issoire (1961) As can be seen there are three pressure-dependant azeotropes which contribute to the difficulty of separating the purified amines from each other and ammonia. These azeotropes demonstrate the strong liquid phase interactions that make the liquid highly non-ideal, and hence difficult to model. Table 3.4: Example of Methylamines Vapour Density Pressure Temperature Ideal Gas Law

    Density Vapour Density Measured Ref. Kenner and Felsing (1939)

    25 bara 125C 23 kg/m3 28 kg/m3 The vapour density is highly non ideal which makes modelling the system more complicated. Methylamines and ammonia are highly hydroscopic; they partly dissociate in water to form basic solutions.

  • Table 3.5: Dissociation of ammonia and methylamines in water at 25C System Kb at 298K Reference NH3 + H2O NH4

    + + OH- 1.8 x 10-5 G Solomons (1988) (CH3)NH2 + H2O (CH3)NH3

    + + OH- 4.4 x 10-4 G Solomons (1988) (CH3)2NH + H2O (CH3)2NH2

    + + OH- 5.2 x 10-4 G Solomons (1988) (CH3)3NH + H2O (CH3)3NH

    + + OH- 5.0 x 10-5 G Solomons (1988) Table 3.5 shows that DMA is the most strongly dissociated of the 4 chemicals. Figure 3.1: Graph showing Txy diagram for MMA and water.

    VLE of MMA /H2O at about 14 bara

    70

    90

    110

    130

    150

    170

    190

    210

    0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00Mol Frac MMA

    T (

    C)

    Graph 3.1 shows that small quantities of water have a strong impact on the dew point of mixtures of water and MMA.

    3.1 Getting the basis correct There is little advantage in having a complicated VLE model if the fundamental physical properties are wrong. An accurate vapour pressure model for pure components is therefore essential. The approach was to regress accurate VLE into the model and then use the model within the known range of accuracy. This was valid providing the experimentally measured ranges were close to expected process conditions in industrial distillation units. Figure 3.2 Schematic Flowchart of DPTs approach to methylamines VLE modelling

    A. Use VLE from literature to build a preliminary model

    B. Use model to choose experimental data that is needed to model distillations accurately.

    Use preliminary model to guide experiments.

    C. Experimental determination of VLE.

    Use preliminary model to help assess if results seem reasonable.

    D. Regress VLE into Model.

    E. Test Model. Experimental VLE at tray composition

    Poor fit

    Good fit

    Use model for design for flow schemes within ranges of known

    accuracy.

    For designs outside ranges of known accuracy check final results with further experiments.

    Experimental VLE at tray composition.

  • 3.2 VLE data is necessary for accurate modelling Temperature, pressure and liquid composition data (TPx data) are readily measured and can be generated by charging known quantities into a vial, heating to a known temperature and recording the pressure. Hence, it is possible to get accurate results quickly and without analysis. However, this simple approach would not have produced an adequate model for the methylamines system. It was realised that, since the vapour phase was strongly non-ideal, it was essential to know the vapour composition accurately. The only option was to design a system that would produce temperature, pressure, liquid composition and vapour composition data (TPxy data). Constant pressure data has traditionally been collected by DPT and so the following data was measured:

    Binary data which could be regressed. Ternary and higher order data to test the accuracy of the model. An accurate mass balance over the VLE unit. Specific tray compositions were tested on the unit.

    After analysis and regression of data from literature a preliminary model was developed. To make the job of doing the experiments as easy as possible, results from a literature survey were used to prepare background information on the system. This included:

    Boiling temperatures of pure components at pressure. Position of any azeotropes known by literature. Model-predicted distillation curves.

    Experience suggested that, even if huge quantities of data for a distillation model were collected, the ultimate number of trays predicted would depend on just a small fraction of this data. This led to two important conclusions. Firstly, the critical areas of a column should be identified so that the design does not rely on just a few experimental points. Secondly, the data requirements can be minimised in non-critical areas. The following strategy was used to identify the critical regions in which to generate data:

    Search literature for VLE and azeotropic data. Regress literature data. Prepare preliminary model. Use preliminary model to simulate the distillation. Identify compositions that are critical to the design of each column. Choose first phase of binary and higher order data that will be experimentally

    determined. It was expected that this first phase of experiments would generate all the data needed for a satisfactory model because the process of model improvement is cyclic. In addition minor components build up in the distillation scheme and have a significant impact on distillation energy requirements. Furthermore, some of the literature data was of poor accuracy and this was not surprising given the problems that were faced during experimentation.

    4 Analytical Techniques and Equipment Description When the portfolio of amines technologies were acquired, the associated analytical procedures were outdated and so DPT developed new procedures using modern techniques. DPT research chemists encountered and overcame a number of technical problems when they attempted to generate the VLE data for this system. Accurate sampling was a problem when dealing with high pressure mixtures of methylamines. Methylamines are toxic and flammable and they have a very low odour threshold limit. The multi-component mixture at high pressure will flash if the pressure is let down when a sample is taken.

  • The first attempt at sampling used a specially designed syringe for taking samples at high pressure. A valve on the syringe allows the contents to be kept at pressure while it is taken to the GC. The syringe was pushed through a rubber septum that was attached to the sample point. This method suffered from failure of the septum due to chemical attach of the rubber by amines. Amines were released into the fume cupboard which was obviously very undesirable, hence a redesign of the sample point was required. Figure 4.1: A sample point and schematic diagram.

    . The three way valve (B) was opened to purge the capillary line. The end of the capillary line was placed into a 2ml sealed sample container that had been charged with a solvent. The solvent was used to stabilise the sample to prevent loss of sample due to flashing at low pressure. The solution was then injected into the GC. There is a balance to be made between the loss of accuracy due to dilution and the loss of accuracy due to insufficient solvent to stabilise the sample. The quantity of solvent was varied depending on the expected composition of the sample. In most cases, ethanol was used as the solvent. One key factor in the successfully measurement of VLE is the design of the equilibrium flash pot. This was based on a design which had been successfully operated on another unit. Initially good results for binary systems that had water and one amine were obtained. However, when the system was switched to a binary system with two methylamines the results were poor indicating a fundamental problem in the VLE separator. The liquid head generated by the low density amine was not sufficient to provide a liquid seal so the separator was modified to overcome this problem. The key modification was to increase the size of the liquid collection vessel. The enlarged vessel ensured a liquid seal was maintained. An accurate mass balance over the rig allowed internal checking of results giving a high degree of confidence that the results were accurate. Product flows, composition and feed flows were measured at near-adiabatic conditions by balancing heat supplied to the VLE separator with heat loss, by wrapping it with heating coils and insulating it. In calibration runs, the unit gave accurate results for a known system with a similar boiling range to the methylamines. Like most of the larger pilot plants at DPTs Technology Centre, the apparatus was DCS controlled. The key benefit of this is accurate temperature control within the VLE separator. In addition the feed pump, safety trips and level control could be left in automatic for hours so that it was very nearly at equilibrium before samples of vapour and liquid were taken. Several samples could be taken at a single condition.

  • Figure 4.1: Photo of the DPT High Pressure VLE Rig Figure 4.3 Diagram of the VLE Apparatus.

    5 Confirmation of Simulation Model The preliminary model used the ideal gas equation for the vapour and NRTL liquid activity coefficients for the liquid. This was appropriate given the accuracy of the information available in literature. Two different models were then tested, namely: NRTL + ideal gas (NRTL-Ideal) and NRTL + SRK-Simsci modified (NRTL-SRKM). The NRTL-Ideal model did not accurately predict all the binary VLE systems accurately. NRTL-SRKM was able to get very accurate fits for all systems. The NRTL-Ideal model gave a better fit to the higher order VLE (3 and more components), however the difference between the fit obtained using the two models was fairly marginal. The strongly non-ideal vapour is not modelled accurately by the ideal gas equation of state. Confidence in the model was gained by measuring three component data. These data were then used to test the binary fitted model and, where necessary the binary parameters were adjusted to achieve a better fit. Experimental multi-component VLE data at very close to actual tray compositions at several locations within the distillation columns were collected. The table below gives an example of the closeness of fit achieve between model and experiment on two trays in the extraction column. Table 5.1: Comparison between experimental results and predicted tray compositions

    Difference between model and Exp. Compositions (mol fraction) Column Temp C

    MMA DMA Water Ammonia TMA

    Extraction 86 0.013 0.008 0.010 0.000 0.015

    Extraction 92 0.006 0.016 0.011 0.000 0.002

    The model results showed a good correlation with industrial plant data. Through the exercise of modelling experimental trays it was possible to demonstrate the strengths and weaknesses of the model. Perfect correlations between experiment plus model and plant data were not achieved but this is a useful tool for design and for trouble shooting or plant de-bottlenecking. This has confirmed that the approach to model selection is valid. The VLE unit is a valuable resource for generation of multi-component high pressure VLE of toxic substances. It has been successfully used to develop an optimised design for an alternative process for the production of improved quality tetrahydrofuran. Moreover, the test unit can be made available for contract design and optimisation studies of a wide range of distillation systems.

  • 5.1 Example Reduction in Steam Requirement for the Methylamines Flowsheet Conventional industrial scale distillation columns for amines are relatively large compared to their production capacity and utility costs are a significant component of the manufacturing cost. Steam consumption also depends heavily on the split of mono, di and tri drawn as product. The new VLE model provided confidence to reduce steam costs by $50 to $70 per tonne by making small changes to the process design. The original four column design by Leonard has been repeated many times but other arrangements of distillation columns have been proposed in patents. These have been evaluated as alternative arrangements. US Patent 2,848,386 describes the following flow-scheme for producing anhydrous MMA from a mixture of methylamines. If an operator requires only MMA product, then DMA and TMA can be recycled without the need to isolate DMA and TMA. When this flow-scheme is compared with the Leonard scheme it can be seen that there is one less column. However, simulations using the DPT model have shown that it is difficult to get high purity MMA using this scheme, and steam usage doesnt represent a significant saving over the Leonard Scheme. Having said this, there are certain combinations of reactor product splits and plant capacity where the benefits of this arrangement are accentuated. Figure 7.1: Copy of US Patent 2,848,386 Fig.1. Figure 7.2: Diagram from US Patent 2,999,053

    US Patent 2,999,053 describes a distillation arrangement where extraction water is fed to a number of positions in a distillation column as shown in the diagram. This arrangement has an advantage over the Leonard flow scheme because it achieves in one column what the Leonard scheme requires two columns to undertake. However, model simulations show that it is actually quite difficult to remove the TMA and ammonia from the MMA, DMA, water and methanol using this arrangement. In addition, significant quantities of DMA are lost overhead. If TMA is not required as a product, an economic evaluation of the benefits to a particular client can be designed for a particular reactor product split and plant capacity.

    5.2 Improvements in Distillation made by DPT DPT has a number of proprietary arrangements of distillation systems to meet the various requirements of industrial plant operators. As described above, a producer may be interested in a methylamines unit for a dedicated purpose such as monomethylamine for an n-methyl pyrrolidone plant. It would not be sensible to purify the trimethylamine and dimethylamine to high purity if these are going to be recycled. Currently, DPT is investigating how best to manage its intellectual property in this area, but already the work described in this paper has yielded a solution for dedicated mono, di and tri methylamine systems and various combinations of these products. Some of these arrangements have already been commercially proven, for example a 2-column design for an MMA dedicated plant.

  • Other improvements resulting from an accurate simulation capability are:

    The unit can be heat confidently integrated with the rest of the plant. DPT can accurately predict tray temperatures and compositions. Plants can be effectively debottlenecked to maximise output from existing equipment.

    6 Impact on Other DPT Technologies The analytical procedures described in this paper have also been used to accurately undertake catalyst research into a range of methylamine and higher alkylamine aminations, enabling a greater understanding of catalyst performance over a wide range of operating conditions. It is apparent that the accurate handling of amines in the laboratory is not easy and requires specific techniques and these skills are currently both within the methylamines process and through aminations to a wide range of derivatives. Since acquiring the amine technologies DPT has been able to significantly reduce the costs of amine production and also the environmental impact of these processes. Two notable additional derivatives to the portfolio of licensable technologies are the solvent n methyl pyrrolidone (NMP) and methyl diethanolamine (MDEA) which is increasingly the solvent of choice for gas treatment. These techniques are not unique to amination processes and similar approaches have been taken to many of the companys licensed technologies that include pressure or vacuum distillation. DPT has demonstrated that an accurate process simulator is a cornerstone for developing and commercialising process technologies in a cost effective, efficient and timely manner.

    7 Conclusion Davy Process Technology has modelled carefully selected physical phenomenon in a range of distillation schemes by rigorously using the most the up-to-date modelling theory. Through appropriate use of laboratory tests, a practical model has been developed that is suitable for designing methylamine plants. This pragmatic and practical approach is a cost-effective balance between the pursuit a perfect model and maintaining control over research costs. The use of such models with targeted experimental data provides an extremely high level of confidence to optimise plant design.

    8 References Andrews, E.A., Overbrook, Spence, L. R., 1938. Separation of Methylamines. U.S. Patent 2,126,600. Babcock, D.F., 1936. Separation of Dimethyl and Trimethylamines by Distillation. U.S. Patent 2,049,486 Graham Solomons, T.W., 1988. Organic Chemistry, Fourth Edition, John Wiley & Sons, New York. pp. 886-887. Hacker, Lucus and Gelbin, 1964, Chem. Tech. (Berlin) 16; C.A. 61, 1528. Horsley, L.H. (1973) Azeotropic Data-III, Advances in Chemistry Series 116., American Chemical Society, Washington, D.C. Issoire,J. and Pfertzel,R., 1961. Chim.Ind. Paris, 86 p.101 Kenner, C.T. and Felsing, W.A., 1939. The Pressure-Volume-Temperature Relations for Gaseous Monomethylamine. J. Am. Chem. Soc., 61(9), pp.2457-2459. Rohm and Hass Co., 1949. Physical Properties of the Methylamines. 1949. Verschueren, K., 1977. Handbook of Environmental Data on Organic Chemicals. Van Nostrand Reinhold Company, New York.

  • For further details please contact:

    Davy Process Technology Limited20 Eastbourne terraceLondon W2 6LEUK

    Tel: +44 (0)20 7957 4120Fax: +44 (0)20 7957 3922Mail: [email protected]: www.davyprotech.com

    Davy Process Technology LimitedTechnology CentrePrinceton DriveStockton-on-TeesTS17 8PYUK

    Tel: +44 (0) 1642 853 800Fax: +44 (0) 1642 853 801Mail: [email protected]: www.davyprotech.com

    Davy Process Technology is a Johnson Matthey company