Programa doutoral em Engenharia da Refinação, Petroquímica e Química Engenharia de Processos e Sistemas Process Simulators Fernando G. Martins Departamento de Engenharia Química Faculdade de Engenharia da Universidade de Porto FGM (FEUP) - February 2011 Slide #1 Module objective and module contents Module objective To present the potentialities of software tools to solve problems related with design and revamping of chemical processes. Module contents Overview of process simulation; Comparison between hand and computer calculation; Types of chemical process problems; Solution of problems in steady-state mode; Systematic methodology in process simulation; Process simulators examples. FGM (FEUP) February 2011 Slide #2 teste 1
Process simulation - I Simulation is the tool that chemical engineers use: To analyse process flowsheets; To locate process malfunctions; To predict the performance of the processes. Mathematical models are the basis for simulation which correspond a collection of equations that relate the process variables, such as stream temperature, pressure, flow rate, and composition, to surface area, valve settings geometrical configuration, and so on. FGM (FEUP) February 2011 Slide #3 Process simulation - II Simulation models can be composed by different levels of complexity involving material balances, material and energy balances, equipment sizing and profitability analysis; Additional equations are added at each level. New variables are introduced and the equation-solving algorithms become more complicated; Most chemical process involve conventional process equipment: Heat exchangers; Pumps; Distillation columns; and so on. FGM (FEUP) February 2011 Slide #4 teste 2
Process simulation - III For the process units referred in the previous slide: The equations do not differ among chemical processes; The physical and thermodynamic properties and chemical kinetic constants differ, but not the equations. It is possible to develop one or more equation-solving algorithms for each process unit to solve the material and energy balances and to compute equipment sizes and costs. These algorithms are the heart of process simulators. These algorithms are often referred as procedures, modules or blocks. FGM (FEUP) February 2011 Slide #5 The importance of the process simulation Conception/Design: Analysis of different process conditions and calculation of operational variables; Start-up: Prediction of operational conditions through the plants start-up; Operation: Studies of the limit operation conditions and changes in project specifications; Optimization: Changing of the operation parameters to process optimization attending to economic, energy, time and environment objectives. FGM (FEUP) February 2011 Slide #6 teste 3
Main steps in process simulation Problem definition Analysis of the results Process model development Solving model equations Additional data collection FGM (FEUP) February 2011 Slide #7 Problem definition which can be selected from simulator? Components; Unit operations; Process flowsheet; Libraries Unit operation models; Models to estimate termophysical properties; Equation solving methods. FGM (FEUP) February 2011 Slide #8 teste 4
Problem definition required information Components; Unit operations; Process flowsheet; Thermophysical properties estimation; Data that must be knowing: Data for input streams; Equipment data; Operation data. FGM (FEUP) February 2011 Slide #9 Types of process simulation problems Flowsheeting; Specification; Optimization; Synthesis. FGM (FEUP) February 2011 Slide #10 teste 5
Flowsheeting problem Inputs Outputs Flowsheet Operational conditions Equipment parameters Calculation of all output information and some internal variables using all information from the inputs. FGM (FEUP) February 2011 Slide #11 Specification problem- performance Inputs Outputs Flowsheet Operational conditions Equipment parameters Some data from the outputs are specified. The other variables are predicted from models. Some data from inputs needn't be specified. FGM (FEUP) February 2011 Slide #12 teste 6
Optimization problem Data: - Feed composition - Feed flowrate Select: -Target product composition -Column trays, feed composition Minimize Objective=f(yield, energy, capital costs,...) FGM (FEUP) February 2011 Slide #13 Synthesis problem Inputs? Outputs Inputs and outputs are known but the flowsheet, the equipment parameters and the operational conditions are unknown. FGM (FEUP) February 2011 Slide #14 teste 7
Example of a synthesis problem Inputs Ethanol Water Technology? Design? Outputs Ethanol Water Separation technology distillation, flash, extraction, separation based on membranes. How many unit operations are needed? How is the equipment design performed? FGM (FEUP) February 2011 Slide #15 Solution of problems in steady-state mode- summary Sequential-modular approximation Each unit operation is simulated at once The flowsheet is decomposed Iterative procedures using tear-streams Less flexible but more robust The initialization is important Memory requirements not very high Equation-oriented approximation All unit operations are simulated at once The equations are sorted All variables are updated at once More flexible but less robust The initialization is much important Memory requirements may be very high FGM (FEUP) February 2011 Slide #16 teste 8
Systematic methodology in process simulation Data collection and reconciliation; Perform additional measures if necessary; Creation/adaptation of models of the equipments involved; Model validation; Model optimization. FGM (FEUP) February 2011 Slide #17 Modular process simulator - I Databases (Termophysical properties, model parameters, etc) Model libraries Properties estimation Simulator core Numerical methods Cost models Interfaces to introduce information and to see results FGM (FEUP) February 2011 Slide #18 teste 9
Modular process simulators - II Computer-aided process design programs, often referred as process or simulators, flowsheet simulators or flowsheeting packages, are widely used in process design; These packages are comprised of the data banks, physical properties models, and equipment operation and sizing models; The extensive data banks contain data on the thermophysicaland transport property constants for hundreds of chemicals, equipment sizing, capital and operating costs and profitability measures; The simulators contain many models of the reactors and unit operation, so-called simulation models that can be used to calculate material and energy balances. FGM (FEUP) February 2011 Slide #19 Modular process simulators - III Simulators sometimes give wrong results, even though no error messages appear. Therefore, simulation results need to be checked carefully before being used as a basis for process and equipment design; It is particularly important to verify the heat and mass balances for any simulation. Otherwise, you might develop an incorrect design; The checks that must be done: Input data are units and numerical values correct; Model scope Is the simulator model scope sufficient to define the problem and thus obtain meaningful results; Thermophysicalproperty models Is the vapor/liquid equilibrium model used appropriate for the mixture being modelled and for the range of temperatures, pressures and compositions simulated; FGM (FEUP) February 2011 Slide #20 teste 10
Modular process simulators - IV The checks that must be done (cont.): Thermophysicalproperties computed Are calculated values of operating conditions and stream properties reasonable for all streams; Specifications Did the simulator converge on all specifications; Process equipment Are the parameters and variables used for sizing and specifying such equipment reasonable? Are the equipment sizes reasonable? In conclusion If a process simulator is used properly and well, the results can be very beneficial; if not use careful and wisely, the consequences may be dire. FGM (FEUP) February 2011 Slide #21 teste 11