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The process simulation is used for the design, development, analysis, and optimization of technical processes and is mainly applied to chemical plants, but also to power stations, and similar technical facilities.

Main principle

Process flow diagram of a typical amine treating process used in industrial plants

The process simulation is a model-based representation of chemical, physical, biological, and other technical processes and unit operations in software. Basic prerequisites are a thorough knowledge of chemical and physical properties^[1] of pure components and mixtures, of reactions, and of mathematical models which, in combination, allow the calculation of a process in computers.

Process simulation software describes processes in flow diagrams where unit operations are positioned and connected by product or educt streams. The software has to solve the mass and energy balance to find a stable operating point. The goal of a process simulation is to find optimal conditions for an examined process. This is essentially an optimization problem which has to be solved in an iterative process.

The process simulation always uses models which introduce approximations and assumptions but allow the description of a property over a wide range of temperatures and pressures which might not be covered by real data. Models also allow to interpolate and extrapolate - within certain limits - and enables the search for conditions outside the range of known properties.

Modelling

The development of models^[2] for a better representation of real processes is the core of the further development of the simulation software. Model development is done on the chemical engineering side but also in control engineering and for the improvement of mathematical simulation techniques. Process simulation is therefore one of the few fields where scientists from chemistry, physics, computer science, mathematics, and several engineering fields work together.

Aa lot of efforts are made to develop new and improved models for the calculation of properties. This includes for example the description of

thermophysical properties like vapor pressures, viscosities, caloric data, etc. of pure components and mixtures
properties of different apparatuses like reactors, distillation columns, pumps, etc.
chemical reactions and kinetics
environmental and safety-related data

Two main different types of models can be distinguished:

Rather simple equations and correlations where parameters are fitted to experimental data.
Predictive methods where properties are estimated.

The equations and correlations are normally preferred because they describe the property (almost) exactly. To obtain reliable parameters it is necessary to have experimental data which are usually obtained from factual data banks^[3]^[4] or, if no data are publically available, from measurements.

Using predictive methods is much cheaper than experimental work and also than data from data banks. Despite this big advantage predicted properties are normally only used in early steps of the process development to find first approximate solutions and to exclude wrong pathways because these estimation methods normally introduce higher errors than correlations obtained from real data.

Process simulation also encouraged the further development of mathematical models in the fields of numerics and the solving of complex problems.^[5]^[6]

History

The history of process simulation is strongly related to the development of the computer science and of computer hardware and programming languages. First working simple implementations of partial aspects of chemical processes have been made in the 1970 where, for the first time, suitable hardware and software (here mainly the programming languages FORTRAN and C) have been available. The modelling of chemical properties has been started already much earlier, notably the cubic equation of states and the Antoine equation are developments of the 19^th century.

Steady state and dynamic process simulation

For the first years the process simulation only has been used to calculate steady state processes. The simulation retrieved a mass and energy balance of a stationary process but any changes over time had to be ignored.

This static process simulation has later been extended by a dynamic simulation. Dynamic means in this context that the time-depending description. prediction and control of real processes in real time has become possible. This includes the description of starting up and shutting down a plant, changes of conditions during a reaction, holdups, and more.

The dynamic simulation needs much more calculation time and is mathematically more complex that a steady state simulation. It can be seen as a multiply repeated steady state simulation with constantly changing parameters.

References

^ Rhodes C.L., “The Process Simulation Revolution: Thermophysical Property Needs and Concerns”, J.Chem.Eng.Data, 41, 947-950, 1996
^ Gani R., Pistikopoulos E.N., “Property Modelling and Simulation for Product and Process Design″, Fluid Phase Equilib., 194-197, 43-59, 2002
^ Marsh K., Satyro M.A., “Integration of Databases and their Impact on Process Simulation and Design”, Conference, Lake Tahoe, USA, 1994, 1-14, 1994
^ Wadsley M.W., “Thermochemical and Thermophysical Property Databases for Computational Chemical Process Simulation”, Conference, Korea, Seoul, August 30 - September 2, 1998, 253-256, 1998
^ Saeger R.B., Bishnoi P.R., “A Modified 'Inside-Out' Algorithm for Simulation of Multistage Multicomponent Separation Processes Using the UNIFAC Group-Contribution Method”, Can.J.Chem.Eng., 64, 759-767, 1986
^ Mallya J.U., Zitney S.E., Choudhary S., Stadtherr M.A., “Parallel Frontal Solver for Large-Scale Process Simulation and Optimization″, AIChE J., 43(4), 1032-1040, 1997

[1] Rhodes C.L., “The Process Simulation Revolution: Thermophysical Property Needs and Concerns”, J.Chem.Eng.Data, 41, 947-950, 1996

[2] Gani R., Pistikopoulos E.N., “Property Modelling and Simulation for Product and Process Design″, Fluid Phase Equilib., 194-197, 43-59, 2002

[3] Marsh K., Satyro M.A., “Integration of Databases and their Impact on Process Simulation and Design”, Conference, Lake Tahoe, USA, 1994, 1-14, 1994

[4] Wadsley M.W., “Thermochemical and Thermophysical Property Databases for Computational Chemical Process Simulation”, Conference, Korea, Seoul, August 30 - September 2, 1998, 253-256, 1998

[5] Saeger R.B., Bishnoi P.R., “A Modified 'Inside-Out' Algorithm for Simulation of Multistage Multicomponent Separation Processes Using the UNIFAC Group-Contribution Method”, Can.J.Chem.Eng., 64, 759-767, 1986

[6] Mallya J.U., Zitney S.E., Choudhary S., Stadtherr M.A., “Parallel Frontal Solver for Large-Scale Process Simulation and Optimization″, AIChE J., 43(4), 1032-1040, 1997

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[2]

[3]

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[5]

[6]

@@ Line 1: / Line 1: @@
-The '''process Simulation''' is a technique for the design, development, analysis, and [[optimization]] of technical processes and is mainly used for [[chemical plant]]s and for power stations.
+The '''process simulation''' is used for the design, development, analysis, and optimization of technical processes and is mainly applied to [[chemical plant]]s, but also to [[power station]]s, and similar technical facilities.
-== Main principles ==
+== Main principle ==
+[[Image:AmineTreating.png|thumb|Process flow diagram of a typical amine treating process used in industrial plants]]
-The process simulation is mainly a '''model'''-based representation of chemical or physical processes and [[unit operation]]s in software. Basic prerequisites are a thorough knowledge of chemical and physical properties and of mathematical, mainly numerical, models which, in combination, allow the calculation of the processes in computers.
+The process simulation is a '''model'''-based representation of [[Chemistry|chemical]], [[Physics|physical]], [[Biology|biological]], and other technical processes and [[unit operation]]s in software. Basic prerequisites are a thorough knowledge of chemical and physical properties<ref>Rhodes C.L., “The Process Simulation Revolution: Thermophysical Property Needs and Concerns”, J.Chem.Eng.Data, 41, 947-950, 1996</ref> of pure components and mixtures, of reactions, and of mathematical models which, in combination, allow the calculation of a process in computers.
+Process simulation software describes processes in [[process flow diagram|flow diagram]]s where [[unit operation]]s are positioned and connected by product or educt streams. The software has to solve the [[mass balance|mass]] and [[energy balance]] to find a stable operating point. The goal of a process simulation is to find optimal conditions for an examined process. This is essentially an [[Optimization (computer science)|optimization]] problem which has to be solved in an iterative process.
-It is important to understand that the simulation does always use '''models''' which include approximations and assumptions. The development of models for a better representation of the actual real process is the core of the further development of the simulation software. Model development is done on the chemical process engineering side but also in control engineering and for the improvement of simulation techniques. Process simulation is therefore one of the few fields where people from [[chemistry]], [[physics]], [[computer science]], [[mathematics]], and several [[engineering]] fields work together.
+The process simulation always uses models which introduce [[approximation]]s and assumptions but allow the description of a property over a wide range of temperatures and pressures which might not be covered by real data. Models also allow to [[interpolation|interpolate]] and [[extrapolation|extrapolate]] - within certain limits - and enables the search for conditions outside the range of known properties.
 == Modelling ==
+The development of models<ref>Gani R., Pistikopoulos E.N., “Property Modelling and Simulation for Product and Process Design″, Fluid Phase Equilib., 194-197, 43-59, 2002
-Since the process simulation relies so heavily on models a lot of efforts have been made in the scientific community to develop new and improved models for chemical and physical properties. This includes for example the description of
+</ref> for a better representation of real processes is the core of the further development of the simulation software. Model development is done on the chemical engineering side but also in control engineering and for the improvement of mathematical simulation techniques. Process simulation is therefore one of the few fields where scientists from [[chemistry]], [[physics]], [[computer science]], [[mathematics]], and several [[engineering]] fields work together.
-* thermophysical properties like vapor pressures, viscosities, caloric data, etc. of pure components and mixtures
-* properties of the different apparatuses like reactors, distillation columns, pumps, etc.
+Aa lot of efforts are made to develop new and improved models for the calculation of properties. This includes for example the description of
-* chemical reactions and kinetics
+* thermophysical properties like [[vapor pressure]]s, [[viscosity|viscosities]], caloric data, etc. of pure components and mixtures
+* properties of different apparatuses like reactors, distillation columns, pumps, etc.
+* chemical reactions and [[kinetics]]
 * environmental and safety-related data
-Two different types of models can be distinguished:
+Two main different types of models can be distinguished:
-# Rather simple equations where parameters are fitted to experimental data.
+# Rather simple equations and [[correlation]]s where parameters are fitted to experimental data.
 # Predictive methods where properties are estimated.
+The equations and correlations are normally preferred because they describe the property (almost) exactly. To obtain reliable parameters it is necessary to have experimental data which are usually obtained from factual data banks<ref>Marsh K., Satyro M.A., “Integration of Databases and their Impact on Process Simulation and Design”, Conference, Lake Tahoe, USA, 1994, 1-14, 1994</ref><ref>Wadsley M.W., “Thermochemical and Thermophysical Property Databases for Computational Chemical Process Simulation”, Conference, Korea, Seoul, August 30 - September 2, 1998, 253-256, 1998</ref> or, if no data are publically available, from [[measurement]]s.
-The equations are preferred because they describe the property (almost) exactly. There are also limitations because of simplifications.
+Using predictive methods is much cheaper than experimental work and also than data from data banks. Despite this big advantage predicted properties are normally only used in early steps of the process development to find first approximate solutions and to exclude wrong pathways because these estimation methods normally introduce higher errors than correlations obtained from real data.
-Process simulation also boosted the development of mathematical models in the fields of numerics and for solving complex problems.
+Process simulation also encouraged the further development of mathematical models in the fields of [[numerics]] and the solving of complex problems.<ref>Saeger R.B., Bishnoi P.R., “A Modified 'Inside-Out' Algorithm for Simulation of Multistage Multicomponent Separation Processes Using the UNIFAC Group-Contribution Method”, Can.J.Chem.Eng., 64, 759-767, 1986</ref><ref>Mallya J.U., Zitney S.E., Choudhary S., Stadtherr M.A., “Parallel Frontal Solver for Large-Scale Process Simulation and Optimization″, AIChE J., 43(4), 1032-1040, 1997</ref>
 == History ==
-The history of process simulation is strongly related to the development of computer science and the hardware and programming developments. First working simple implementations of partial aspects have been made in the 1970 where for first time suitable hardware and software (here mainly the programming languages [[FORTRAN]] and [[C]]) have been available. The modelling of chemical properties has been started already much earlier, notably the cubic [[equation of states ]] and the [[Antoine equation]] are developments of the 19<sup>th</sup> century. Chemical reactions have also been modelled already and the knowledge of the properties of apparatuses has also been quite good so that all basic information have been available.
+The history of process simulation is strongly related to the development of the [[computer science]] and of computer hardware and programming languages. First working simple implementations of partial aspects of chemical processes have been made in the 1970 where, for the first time, suitable hardware and software (here mainly the programming languages [[FORTRAN]] and [[C (programming language)|C]]) have been available. The modelling of chemical properties has been started already much earlier, notably the cubic [[equation of state]]s and the [[Antoine equation]] are developments of the 19<sup>th</sup> century.
+== Steady state and dynamic process simulation ==
-Together with the development of the process simulation and inspired by it developments of new models and methods for the prediction and characterization of chemical and thermophysical processes have increased. Besides the models and methods factual data banks for storing all these information have been developed.
+For the first years the process simulation only has been used to calculate steady state processes. The simulation retrieved a mass and energy balance of a stationary process but any changes over time had to be ignored.
-== Static and dynamic process simulation ==
-For the first years the process simulation only has been used to calculate static processes. This simulation retrieved a mass and energy balance of a stationary process but any changes had to be ignored.
 This static process simulation has later been extended by a dynamic simulation. ''Dynamic'' means in this context that the time-depending description. prediction and control of real processes in real time has become possible. This includes the description of starting up and shutting down a plant, changes of conditions during a reaction, holdups, and more.
-The dynamic simulation need much more calculation time nad is mathematically way more complex that a static simulation because it can be seen as a multiply repeatd static simulation with constantly changing parameters.
+The dynamic simulation needs much more calculation time and is mathematically more complex that a steady state simulation. It can be seen as a multiply repeated steady state simulation with constantly changing parameters.
+== See also ==
+* [[List of chemical process simulators]]
+* [[List of dynamic process simulators]]
+== References ==
+<references/>