Industrial Process Simulation Software
- Free Modeling And Simulation Software
- Process Modeling And Simulation Software
- Process Simulation Tools
- Industrial Process Simulation Software Downloads
- Process Simulation Software Free
Chemical process simulation software that includes libraries of chemical components, thermodynamic methods, and unit operations to allow steady-state and dynamic simulation of continuous chemical processes from lab scale to full scale. Ideal for users who want to design processes, or rate existing processes, in steady state.
- EQ-COMP is a complex chemical engineering process simulation software tool for automatically calculating vapor-liquid equilibrium properties of pure hydrocarbons and binary and multi-component mixtures of hydrocarbons. EQ-COMP is written using software tools like MS Excel and VBA.
- Software Process simulation modelling: Like any simulation, software process simulation (SPS) is the numerical evaluation of a mathematical model that imitates the behavior of the software development process being modeled. SPS has the ability to model the dynamic nature of software development and handle the uncertainty and randomness inherent in it.
Process simulation is used for the design, development, analysis, and optimization of technical processes such as: chemical plants, chemical processes, environmental systems, power stations, complex manufacturing operations, biological processes, and similar technical functions.
Free Modeling And Simulation Software
Main principle[edit]
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.
Process simulation always use 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 interpolation and extrapolation - within certain limits - and enable the search for conditions outside the range of known properties.
Modelling[edit]
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.
A 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 publicly 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[edit]
The history of process simulation is strongly related to the development of the computer science and of computer hardware and programming languages. Early working simple implementations of partial aspects of chemical processes were introduced in the 1970s when suitable hardware and software (here mainly the programming languages FORTRAN and C) became available. The modelling of chemical properties began much earlier, notably the cubic equation of states and the Antoine equation were precursory developments of the 19th century.
Steady state and dynamic process simulation[edit]
Initially process simulation was used to simulate steady state processes. Steady-state models perform a mass and energy balance of a stationary process (a process in an equilibrium state) it does not depend on time.
Dynamic simulation is an extension of steady-state process simulation whereby time-dependence is built into the models via derivative terms i.e. accumulation of mass and energy. The advent of dynamic simulation means that the time-dependent 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, thermal changes and more.
Dynamic simulations require increased calculation time and are mathematically more complex than a steady state simulation. It can be seen as a multiply repeated steady state simulation (based on a fixed time step) with constantly changing parameters. Display adapter driver windows 10.
Dynamic simulation can be used in both an online and offline fashion. The online case being model predictive control, where the real-time simulation results are used to predict the changes that would occur for a control input change, and the control parameters are optimised based on the results. Offline process simulation can be used in the design, troubleshooting and optimisation of process plant as well as the conduction of case studies to assess the impacts of process modifications. Dynamic simulation is also used for operator training.
Process Modeling And Simulation Software
See also[edit]
- Advanced Simulation Library[7]
References[edit]
- ^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
- ^'ASL: Physical Vapor Deposition Simulation'.
Software Process simulation modelling:Like any simulation, software process simulation (SPS) is the numerical evaluation of a mathematical model that imitates the behavior of the software development process being modeled. SPS has the ability to model the dynamic nature of software development and handle the uncertainty and randomness inherent in it.[1]
Uses of software process simulation[edit]
Following main purposes have been proposed for SPS:[2]
- Support in operational project management (estimation, planning and control)
- Support for strategic management
- Tool for training and education for software project management and software development lifecycle (c.f.[3] and[4]).
- Process improvement and technology adoption
How to do software process simulation[edit]
Software process simulation starts with identifying a question that we want to answer. The question could be, for example, related to assessment of an alternative, incorporating a new practice in the software development process. Introducing such changes in the actual development process will be expensive and if the consequences of change are not positive the implications can be dire for the organization. Thus, through the use of simulation we attempt to get an initial assessment of such changes on the model instead of an active development project. Based on this problem description an appropriate scope of the process is chosen. A simulation approach is chosen to model the development process. Such a model is then calibrated using empirical data and then used to conduct simulation based investigations. A detailed description of each step in general can be found in Balci's work,[5] and in particular for software process simulation a comprehensive overview can be found in Ali et al.[6]
Examples of using software process simulation for practical issues in industrial settings[edit]
- Process assessment: Enabling dynamic analysis in value stream mapping in industrial settings [7]
- Software Testing: Deciding when to automate software testing [8]
Key venues[edit]
Process Simulation Tools
Software process simulation has been an active research area for many decades some of the key venues include the International Conference on Software and Systems Process[9] and its predecessor Workshop on Software Process Simulation Modeling (ProSim) from 1998-2004.[10]
Industrial Process Simulation Software Downloads
References[edit]
- ^Ali, NB; Petersen, K; Wohlin, C (2014). 'A Systematic Literature Review on the Industrial Use of Software Process Simulation'. Journal of Systems and Software. 97: 65–85. CiteSeerX10.1.1.717.3797. doi:10.1016/j.jss.2014.06.059.
- ^Kellner, Marc I; Madachy, Raymond J; Raffo, David M (1999). 'Software process simulation modeling: Why? What? How?'. Journal of Systems and Software. 46 (2–3): 91–105. CiteSeerX10.1.1.587.8752. doi:10.1016/s0164-1212(99)00003-5.
- ^'Use of simulation for software process education: a case study'(PDF).
- ^von Wangenheim, C.G.; Shull, F. (2009). 'To Game or Not to Game?'. IEEE Software. 26 (2): 92–94. doi:10.1109/MS.2009.54.
- ^Osman Balci (2012), 'A Life Cycle for Modeling and Simulation,' Simulation: Transactions of the Society for Modeling and Simulation International 88, 7, 870–883.
- ^Ali, N.B.; Petersen, K., 'A Consolidated Process for Software Process Simulation: State of the Art and Industry Experience,' Software Engineering and Advanced Applications (SEAA), 2012 38th EUROMICRO Conference on , vol., no., pp.327,336, 5-8 Sept. 2012doi: 10.1109/SEAA.2012.69 http://www.bth.se/fou/forskinfo.nsf/0/7e2b9e104c9956cec1257acf006a1282/$file/Consolidated%20process.pdf
- ^Ali, NB; Petersen, K; de França, BBN (2015). 'Evaluation of simulation-assisted value stream mapping for software product development: Two industrial cases'. Information and Software Technology. 68: 45–61. doi:10.1016/j.infsof.2015.08.005.
- ^Garousi, Vahid; Pfahl, Dietmar (2015). 'When to automate software testing? A decision‐support approach based on process simulation'. Journal of Software: Evolution and Process.
- ^'Archived copy'. Archived from the original on 2015-02-21. Retrieved 2014-12-01.CS1 maint: archived copy as title (link)
- ^http://www.verlag.fraunhofer.de/bookshop/artikel.jsp?v=220684