Sequential modular simulator

Equations-Oriented Simulators. In contrast to the sequential-modular simulators that handle the calculations of each unit operation as an iaput—output module, the equations-oriented simulators treat all the material and energy balance equations that arise ia all the unit operations of the process dow sheet as one set of simultaneous equations. In some cases, the physical properties estimation equations also are iacluded as additional equations ia this set of simultaneous equations. 

The essential differences between sequential-modular and equation-oriented simulators are ia the stmcture of the computer programs (5) and ia the computer time that is required ia getting the solution to a problem. In sequential-modular simulators, at the top level, the executive program accepts iaput data, determines the dow-sheet topology, and derives and controls the calculation sequence for the unit operations ia the dow sheet. The executive then passes control to the unit operations level for the execution of each module. Here, specialized procedures for the unit operations Hbrary calculate mass and energy balances for a particular unit. FiaaHy, the executive and the unit operations level make frequent calls to the physical properties Hbrary level for the routine tasks, enthalpy calculations, and calculations of phase equiHbria and other stream properties. The bottom layer is usually transparent to the user, although it may take 60 to 80% of the calculation efforts. 

The computer effort required for convergence depends on the number and complexity of the recycles ia the dowsheet, the nonlinearities ia the physical properties, and the nonlinearities ia the calculation of phase or chemical equiHbria. In sequential-modular simulators these calculations are converged one at a time, sequentially, and ia a nested manner. In equation-oriented simulators they are converged as a group and, ia the case of complex dow sheets involving nonideal mixtures, there could be significant reduction ia computer effort. 

Historically, sequential-modular simulators were developed first. They were also developed primarily ia iadustry. They coatiaue to be widely used. la terms of unit operatioas, each module can be made as simple or complex as needed. New modules can be added as needed. Equation-oriented simulators, on the other hand, are able to handle arbitrary specifications and limitations for the entire process dow sheet more dexibly and conveniendy than sequential-modular simulators, and process optimization can also be carried out with less computer effort. 

The second classification is the physical model. Examples are the rigorous modiiles found in chemical-process simulators. In sequential modular simulators, distillation and kinetic reactors are two important examples. Compared to relational models, physical models purport to represent the ac tual material, energy, equilibrium, and rate processes present in the unit. They rarely, however, include any equipment constraints as part of the model. Despite their complexity, adjustable parameters oearing some relation to theoiy (e.g., tray efficiency) are required such that the output is properly related to the input and specifications. These modds provide more accurate predictions of output based on input and specifications. However, the interactions between the model parameters and database parameters compromise the relationships between input and output. The nonlinearities of equipment performance are not included and, consequently, significant extrapolations result in large errors. Despite their greater complexity, they should be considered to be approximate as well. 

Biegler, L. T. Improved Infeasible Path Optimization for Sequential Modular Simulators—I The Interface. Comput Chem Eng 9 245-256 (1985). 

Biegler. L. T., and Cuthrell, 1. E., Improved infeasible path optimization for sequential modular simulators — II The optimization algorithm, Comp, and Chem. Eng. 9(3), 257-267 (1985). 

Choose a tear stream variable and convert the flowchart into a block diagram for a sequential modular simulation, using blocks MIX. REACT. SEP. and a convergence block CONVC. 

An example of a sequential modular simulation of a relatively large process is given in Example 10.3-3, following a discussion of the second broad approach to process simulation. 

Set up a sequential modular simulation of the process, using the following blocks ... 

Figure lOJ-2 Block diagram for sequential modular simulation of ammonium nitrate process. 

In the past, most simulation programs available to designers were of the sequential-modular type. They were simpler to develop than the equation-oriented programs and required only moderate computing power. The modules are processed sequentially, so essentially only the equations for a particular unit are in the computer memory at one time. Also, the process conditions, temperature, pressure, flow rate, etc., are fixed in time. With the sequential modular approach, computational difficulties can arise due to the iterative methods used to solve recycle problems and obtain convergence. A major limitation of sequential modular simulators is the inability to simulate the dynamic, time-dependent behavior of a process. 

For a sequential-modular simulation program to be able to solve a flowsheet with a recycle, the design engineer needs to provide an initial estimate of a stream somewhere in the recycle loop. This is known as a tear stream, as the loop is torn at that point. The program can then solve and update the tear stream values with a new estimate. The procedure is repeated until the difference between values at each iteration becomes less than a specified tolerance, at which point the flowsheet is said to be converged to a solution. 

CHEOPS obtains this setup file in XML format from ModKit-l-. Tool wrappers are started according to this XML file. The input files required for the modeling tools Aspen Plus and gPROMS are obtained from the model repository ROME. CHEOPS applies a sequential-modular simulation strategy implemented as a solver component because all tool wrappers are able to provide closed-form model representations. The iterative solution process invokes the model evaluation functionality of each model representation, which refers to the underljdng tool wrapper to invoke the native computation in the modeling tool the model originated from. Finally, the results of all stream variables are written to a Microsoft Excel table when the simulation has terminated. 

Figure 2.8 Software architecture of a Sequential-Modular simulator...

Figure 4.11 Genetic algorithms (GAs) sequential modular simulation for the organic Rankine cycle (ORC) [47].

Sheikhi A, Gharebagh RS, Eslami A, Sohi AH. Sequential modular simulation of ethanol production in a three-phase fluidized bed bioreactor. Biochem. Eng. J. 2012 63 95- 103. 

In a sequential modular simulator, the unit models are encapsulated as procedures where the output streams are desired design parameters. These procedures are then solved in a sequence that generally parallels the flow of material of actual process. A remarkable exception is the process simulator HYSYS, for which most unit operations are solved as soon as all the degrees of freedom are satisfied independently of whether those specifications are introduced. 

Figure 13.2 Solution Sequence Using Sequential Modular Simulator for a Process Containing No Recycles...

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