Computer aided process design: Short-cut design for polymer production

Computers chem. Engng Vol.20, Suppl.,pp. $237-$242, 1996

~ ) Pergamon

S0098-1354(96)00050-6

Copyright© 1996 ElsevierScienceLid Printed in GreatBritain.All rightsreserved 0098-1354•96 $15.00+ 0.00

COMPUTER AIDED PROCESS DESIGN: SHORT-CUT DESIGN FOR POLYMER PRODUCTION.

TIMOTHY F. MCKENNA CNRS - L.C.P.P., B.P. 24, 69390 VERNAISON, FRANCE Abstract - An hierarchical procedure tbr the conceptual design and rapid simulation of free radical homo- and copolymerisations in solution is presented. This conceptual design procedure is intended for use as a tool for the understanding and screening of design alternatives, especially by the inexperienced user. It uses the minimum amount of information possible to screen a large series of process alternatives in order to identify potentially optimal process designs, both in terms of economics and product quality (polymer molecular weight, etc.), and to eliminate alternatives that are either physically undesirable or economically unfeasible. Additionally, the computerised version of the programme can be used to perform a sensitivity analysis of candidate designs This procedure allows the user to see what are the most important parameters to be considered, what can be ignored, and where future experimental programmes would be most beneficial Examples of the production of both homo- and copolymers in solution are presented.

SCOPE Over the past ten to fifteen years, a great deal of work has been done in the area of developing computeraided process design tools for typical petrochemical processes. This type of tool is intended to act as an expertsystem, or pseudo-expert system that helps the process engineer select the best combination of unit operations that make up a given chemical process. However, similar efforts for polymer process design are lacking. As pointed out by Kiparissides (1995), very little progress has been made in the development of tools for the design of computeraided design tools for polymerisation systems. In recent years significant progress has been made in the area of the development of mechanistic models of polymer processes, and in the development simulators such as the commercially available ASPENPlus®, or other academic simulators (e.g. Kiparissides, 1995). Nevertheless, in order to use such tools it is necessary to have previously defined a process flow sheet, and be an expert in polymerisation reactor simulation. No true design tools exist that help an inexperienced user learn about polymer process design, including the choice and modelling of ALL types of unit operations. The software tool presented here represents a contribution to the development of a computerised procedure for the design of conceptual process flowsheets for polymer production. Conceptual design refers to the selection of major unit operations such as reactors, flash evaporators, extruders and compressors, as well as their interconnections and operating conditions, but does not include aspects such as piping layouts and pumps. This type of tool is not intended to immediately replace large process simulators, but rather to allow users to quickly and efficiently design process flowsheets, and understand the important interactions and aspects before proceeding with the final design. The design procedure illustrated in Figure l is based on a level-by-level approach, with the process flowsheet, economic evaluation and product information being refined at each level, and uses short-cut calculations and heuristics wherever possible. The underlying idea is that one supplies the minimum amount of information possible in order to eliminate unfavourable process alternatives at the earliest possible stage - thereby requiring the user to supply only that information that is needed. For example, if it turns out that a process alternative cannot earn a profit for any given conversion - even without designing a separation system - it is not necessary to waste time and resources simulating the next level of the procedure. Rather it is preferable to examine an alternative design for the reactor system. A very brief outline of the design procedure itself follows. Details can be found elsewhere (e.g. McKenna and Malone, 1990, 1995; McKenna, 1990, 1995). While the Levels used in the design procedure and the hierarchical refinement of the design itself are similar to that developed by Douglas (1985), the rules (heuristics) defined, equipment considered, and the distributive nature of the final properties of the products considered here are very different for polymerisation processes. Level 0 is intended primarily as an organisational platform for the computerised version of the design process, or as an organisational aid for the engineer. At this Level the physical property data for all components, the kinetic mechanism (no rate constants are required yet), the method of polymerisation, the order of the polymerisation, the form of

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the final product, the utility levels and costs, capital cost correlations and plant operating conditions are specified. This information is included here because it is common to many of the later stages of design. Additional information will be required at each Level. Level I is where the choice of operational mode is made. Several heuristics, outlined in Table I, are used to help make this choice and are ordered in an "if-then-else" sequence, where the decision is made from heuristic I if possible, if not, with heuristic 2, etc. until the mode is defined.

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Preliminary Design Figure 1. Structure of design procedure presented in current work. E.P. refers to the economic potential which is simply the value of the final product less the sum of the annualised capital and operating costs of the equipment at each level plus the raw material costs. Each level has its own specific set of input information.

Table 1. Batch vs. Continuous Heuristics Heuristics I. Choose batch or continuous according to any process constraints. 2. Choose batch for production rates less than 500 tonnes/yr. 3. Chose continuous for production rates over 10.000 tonnes/yr. 4. Choose batch for new products (ones with which the company has no experience). 5. Choose batch if there are more than la quality/grade changes per year. 6. Choose continuous for polycondensation. 7. Choose continuous for processes with no termination reactions. 8. Choose continuous by default,

Level 2 is where the feed, product, by-product and purge streams are set. Boiling points and component assignations (e.g. product, waste, etc.) are used to test for the number of process streams. At this stage the process is a black box, where the Economic Potential at Level 2 (EP2) is simply the value of the polymer plus the fuel value of the purge less the cost of the raw materials and the annualised capital and operating costs for the recycle and feed compressors. Level 3 is where the reactor configuration and number, a well as the number and destination of the various gas and liquid phase recycle streams are determined. The configuration of the reactor system depends on kinetic and economic considerations, as well as on physical properties such as the viscosity. Various heuristics are available to help

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choose reactor types according to process type and reaction conditions, e.g. for free radical copolymerisations in solution use a continuous stirred tank reactor (to avoid composition drift) with a turbine impdler for viscosities less than 500 poise (heating problems and mixing becomes inadequate). Kinetic models, and viscosity estimates are among the important input information at this Level. The economic potential at Level 3 is: EP3 = EP2 - (annualised reactor costs + operating costs + initiator cost). Level 4 is where the structure of the separation system is defined and the equipment required to isolate and purify the polymer and to recover and recycle solvents and unreacted monomers is considered. A sequence of steps is proposed for these operations based on the phases in the reactor effluent, as well as the concentration and physical properties of the stream. The four combinations of interest are liquid (L), liquid and vapour (L/V), liquid and solid (L/S) and solid and vapour (S/V). The exact choice of equipment depends on the physical nature and concentration of the phases present, e.g. for solutions (L), flash evaporation can be used for viscsosities of less than 10 poise, and extruders must be used at viscosities over 50,000 poises. The economic potential at this level is defined as: EP4 = EP3 - (annualised separation costs + operating costs). Level 5 Energy integration is included for completeness, but is not considered in this work. For continuous processes the energy integration problem has been studied extensively and computer-assisted design tools are available. Level 6 The final step is a dual approach sensitivity analysis, where both local and global sensitivities are calculated, and the importance of maximum errors is examined. This analysis is used to obtain an idea of the economic and product sensitivity, to identify what are the critical parameters in the process design and to explore the relationship between the heuristics used in defining the flowsheet and operating conditions and possible errors in the parameters.

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Figure 2. Final fiowsheet for the production of polyethylene in slurry. The process operates at an economic optimum of 95% conversion and a purge composition of O.7 mole fraction of ethylene. Eth = ethane impurity, H2 = hydrogen (for catalysis). ETY = ethylene monomer, PE = polyethylene product, nHEP = n-heptane solvent. EP4 (below) for the polyethylene example is for a fixed purge composition.

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RESULTS The computerised version of the design procedure can be currently used to conceive and evaluate flowsheets for the continuous production of free radical homo- and co-polymers in solution, and the production of olefin homopolymers in slurry reactors. An example flowsheet and corresponding EP4 are shown in Figure 2 for the optimal polymerisation of ethylene on a heterogeneous catalyst in a heptane slurry. A purge stream is included in the design based on the heuristic: "If there is a recycle stream containing an impurity or a by-product along with a product or a raw material, each with a normal boiling point lower than that of propylene, then there is a vapour phase purge stream." The economic potential is the result of the different economic trade-offs of high recycle and raw material costs at low conversion and high reactor costs at high conversion. This value, a slight function of the purge composition, shows that from an economic point of view, it is preferable to operate the process at 95% conversion. The flowsheet in Figure 2 is representative &the format of the flowsheets as they appear in the computer programme. The flowsheet and graph in Figure 2 demonstrate the capability of the computer programme to reproduce realistic results, both on the process and economic levels - the flowsheet structure and operating conditions are similar to those described in the literature for polyethylene processes using Phillips catalysts (Choi and Ray). While it is not shown on the flowsheet, an operating pressure of just under 40 atmospheres w~s found to be economically optimal (chosen using the sensitivity analysis shown below). The inexperienced user is thus able to obtain both a realistic flowsheet structure based on calculations and heuristics embedded in the desgin procedure and computer code something that is not possible with a process simulator - and realsitic operating conditions based on physical and economic evidence The sensitivity of the results can be examined both locally (e.g. in the immediate vicinity the optimal conversion) and globally. Local errors in a function of several parameters can be estimated via a Taylor series expansion around a fixed point (in this case the "optimal" conversion) as follows;

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where the derivative on the right hand side can be thought of as a sensitivity coefficient, a measure of the local sensitivity of the function P (e.g. the EP4, or Mw) to uncertainty in a given variable. Examples of the local sensitivity of the polyethylene design are given in Table 2. It can be seen that the design is very sensitive to the fash temperature (high separation costs) and compressor prices (high recycle costs), but not to reactor temperature or pressure for instance. Table 2. Localised Sensitivity for the PE Exam )le Parameter

(PJ Rate constant CSTR Temperature Composition of gas phase purge Reactor pressure Flash Temperature Compressor Cost CSTR cost

/~In(EP) ~ln(pi) 0.059 -0.080 0.005 0.02 -0.437 - I. 16 -0.099

One can also use the design software and procedure to evaluate the relationship between economics and molecular weight tbr instance. An example is given in Figure 3 for a styrene-acrylonitrile (SAN) production facility consisting of a stirred tank reactor operating at near 80% conversion (in order to obtain a polymer of a molecular weight near 100,000), followed by a flash drum and a wiped film evaporator to purify the polymer. The reaction takes place in solution, of 10% toluene (v/v) in order to reduce the viscosity.

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It can be seen from Fig. 3 that the EP4 is relatively constant over a wide range of conversion, but the molecular weight of the polymer product obtained varies significantly over this same range. Therefore we are constrained to operate at nearly 80% conversion in order to obtain the quality of product that was specified a priori. Note that this is one of the major differences between polymer production and the production of low molecular weight materials. The mechanical and physical properties of polymers are a strong function of aspects such as the molecular weight and copolymer composition of the molecules formed - characteristics that are a strong function of operating conditions and concentrations. In classic petrochemical processes, important parameters such as yield and purity are functions of the operating conditions, but regardless of what temperature we chose, the benzene that comes out of a reactor, once purified, will always have the same melting point and molecular weight. This is absolutely not true for polymers. The rapid calculation of mass balances and equipment design equations available with the computerised version of the code also makes it possible to investigate the sensitivity of a large number of candidate designs, both locally and globally. Local sensitivities are useful indications of how the process will behave when confronted with perturbations in operating conditions (temperatures, purities, etc.), and global re-evaluation at limits of uncertainty (e.g. propagation factor +_ 50%) facilitates the screening of candidate designs. Overall global sensitivity results for the SAN example above are given in Table 3. 12(X)00

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Figure 3. EP4 and flowsheet tbr the SAN process. Note that LRS refers to Liquid recovery system, in this case a system of distillation towers that separate the ethylbenzene impurity from the recycled monomer and solvent. If this action turns out to be expensive, a liquid purge stream could be considered as a process alternative,

Proposed structural changes indicated in this table mean that the percentage change in the parameter in question leads to results such that the heuristics built into the programme cause changes to be made in the base case flowsheet (in this example all changes are removal of the flash unit - this makes the separation more expensive). These resuRs also tell us that it is not particularly important to invest a great deal of time and energy in the identification of the styrene propagation constant - it is better to concentrate limited resources on good estimates of the vis-

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cosity. Also, control of the molecular weight is more effective, dollar for dollar, using the reactor temperature than changing the initiator concentration. The results presented here are only a very, brief sample of the parameters that can be tested with the computerised code. Table 3. Overall Sensitivit,, of SAN Example Error % Error in EP4 (Pi) __((Estimate %) Upper limit Lower limit Viscosity +_50 -6.82* 0.32 CSTR temperature _+5 0.32 -0.37 Initiator feed rate _+5 0.09 -6.73* Styrene propagation constant _+50 0.017 -0.033 Mass fiactmn solvent in CS'IK _+ 10 0.063 -6.75" * Indicates Proposed Structural Change in Flowsheet Parameter

% Error in Mw l.p_perlimit Lower limit -0.388 0.444 -4.74 5.24 0.458 -0.69 -7.00 7.53 No influence

CONCLUSIONS The computerised design procedure presented in this work allows one to construct process flowsheets based on the minimum amount of available information, and, to the extent that it can be used by individuals who are inexperienced in the area of polymer processes, it can be considered to serve as a type of pseudo-expert system. The examples presented demonstrate the importance, both in terms of economics and molecular weight development, of kinetic parameters and an understanding of the well-known Tromsdorff effect. In fact, the sensitivity analysis also allows us to identify which variables are economically more viable in controlling both process yield and the development of the molecular weight distribution. SIGNIFICANCE This tool represents one of the first attempts at developing a computer-driven knowledge-based system for the conceptual design of polymer production processes. It can be used to help students and inexperienced engineers understand the important trade-offs involved in polymerisation processes. It represents a useful computer-aided training/teaching tool since it combines certain aspects of simulators with a limited knowledge base and prompts its user to consider the appropriate aspects of the design problem. Thus inexperienced users can use this procedure to guide them through a process design problem, and eventually use the computerised version of the code (which can be continually updated when new knowledge becomes available) to understand the process itself. Furthermore it also treats the entire design problem, dealing with entire process mass balances, and interactions between separation and reaction steps etc A user who does not know what flowsheet structure should be used with a simulator has now obtained one to be explored in more detail. The resulting structure and operating conditions can be then refined with confidence and more efficieully with more powerful simulators, the poor designs having been eliminated with the conceptual design procedure, The introduction of a multi-parameter sensitivity analysis is also a useful tool in identifying key parameters and understanding the importance of the different decisions encoded in the software package. It is of use especially in preparing major simulations since it can be used to generate candidate designs based on heuristics and limited information, enabling the process engineer to eliminate poor, unfeasible designs before costly simulations. LIST OF SYMBOLS EPI, EP2, EP3, EP4 MW P iSp~

Economic Potential at Levels I, 2, 3, 4 ($/yr) Molecular weight of polymer Multi-variable function (e.g. EP, MW) local uncertainty in the value of a parameter.

REFERENCES

Choi, K Y., W. It. Ray, J. M S.-Rev. Macromol. Chem. Phys., C25, I-55 (1985). Douglas, J. M, AI.Ch.E J., 31, pp 353-62, 1985. Kiparissides, C., p. 63 l, 51h Workshop opt t'olymer Reactitm I',)lgiueermg, Dechema Monographs, Vol. 131 (1905). McKenna, T. F. and M F. Malone, Chem. Eng., 14(10), 1127-49, (1990). McKenna, T. F. and M F. Malone, Submitted to Entropie, August, 1995. McKenna, T F., Conceptual Design of Polymerisation Processes, Ph.D. Thesis, University of Massachusetts (1090). McKenna, T. F., Submitted to Eutropie, August, 1995.