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Process Modelling Services

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Contents

Introduction


Austherm Pty Ltd personnel and associates have in-depth experience in the development and in the use of a number of commercial process simulation software systems. Our experience covers a wide range of applications, development of specialist physical properties data, and special programming.

There is more to using many of these packages than just sitting down in front of a computer. Simulation packages range from complete expert systems for a particular process in which the user only has to "fill in the squares" to very general packages which are able to model all or part of any of chemical, energy, environmental or metallurgical systems and which require considerable expertise and understanding to be assured of obtaining meaningful results (see our page on technical auditing). Continue reading to learn more about what we consider to be important in computational process modelling and simulation.

Process simulation is one of the tools which may be applied to problem solving. A problem exists when an opportunity or threat is recognised and one is not sure how best to act in order to take advantage of the one or to counter the other. Problem recognition is of no small importance in which insensitivity may lead at best to missed opportunity and at worst to disaster.

Not only must one be able to solve well defined problems, one must also identify the problems to be solved.

Four steps for managers are:

  1. Problem recognition
  2. Acceptance of responsibility to deal with the problem
  3. A sufficient incentive for action
  4. A belief that the possibility of finding a solution exists

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Models and Problem Recognition


The process of becoming aware of an opportunity or a threat may be analysed in terms of a comparing of models, one of the situation as it is and the second of the situation as it might be. Process simulation is an example of the use of models for analysis.

Models may be:

  • an aid to thought
  • an aid to communication
  • for training and instruction
  • as tools for prediction
  • for control or decision-making processes
  • used to investigate complicated, expensive, dangerous or inconvenient systems
  • used to investigate systems in which study in real time would be a problem
  • used to elucidate operating mechanisms for complex systems
  • used to investigate alternate strategies

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The Modelling Process


The modelling process may consist of the following steps:
  1. Recognise the existence of a problem and decide to tackle it.
  2. Delineate the system to be studied.
  3. Formulate questions to be asked.
  4. Run the model (simulate)
  5. Analyse the results and their implications.
Austherm Pty Ltd personnel are familiar with all steps of the modelling process.

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Choosing Models


Models are used as partial substitutes for their prototypes - to assist in designing, understanding, predicting the behaviour of, or controlling the prototype. In order to perform these functions, they must represent the significant characteristics of their prototype. Which and how many properties are significant in a particular case and how they are to be represented in the model is at the heart of the activity of modelling. That is, A model must be suited to its purpose. A model may be misleading if an essential characteristic of the system has not been represented.

Steady State Simulation is used for process design and optimisation through generation of mass and/or energy balances.

Dynamic Simulation is used for process control, start-up and shut-down.

General Process Simulators and Specific Case Simulators are available. A general process simulator may be used to model the behaviour of a wide variety of processes. A specific case simulator is designed to predict the behaviour of a particular process.

Local Simulators may be used instead of or in addition to Whole Process Simulators. A local simulator is intended to look at a specific part of a process. A whole process simulator is designed to be able to consider a complete process flowsheet.

General Simulation Packages

  • ASPEN PLUS
  • PROCESS / PROII
  • HYSIM
  • DESIGN II
  • CHEMCAD
  • METSIM (general metallurgy)
  • SIMMET (mineral processing)

Local Simulation Packages

  • F*A*C*T
  • GTT - ChemSage, ChemApps
  • Thermochemistry
  • THERMOCALC
  • MTDATA
  • HSC

Specific Case Simulation Packages

  • MAPPS (pulp and paper)
  • SULSIM (Claus process)

An engineer may be required to:

  1. compare all available simulators
  2. select the most suitable simulator or simulators for a project
  3. receive training in the use of a simulator(s)
  4. carry out process simulation(s)
Austherm Pty Ltd personnel are experienced in the choice of suitable models and in the selection and use of a number of process simulators.

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Uses, Benefits, Limitations of Process Simulation


Uses

  • troubleshooting
  • operation optimisation
  • design
  • new technology evaluation

Benefits
When properly used, process simulation has the following benefits:

  • cost reduction
  • improved organisational effectiveness
  • reduction of capital cost by better design
  • reduction of time for design, commissioning and start-up
  • reduction of pilot plant cost, size and complexity
  • material and energy optimisation
  • improved productivity and efficiency
  • provision of training for new personnel
  • provision of a screening method for projects
  • provision of a repository for technical knowledge
  • definition of gaps, deficiencies and inconsistencies in process knowledge
a) In Existing Processes
Troubleshooting
  1. debottleneck
  2. analyse process measurements
  3. determine sites of losses of energy, materials
  4. determine actual flows and equipment loadings
  5. locate instrument errors
Optimisation
  1. optimise flowsheet
  2. optimise unit operation
  3. optimise operation economically
  4. evaluate alternative raw materials
  5. optimise location and flow of recycle streams
  6. develop seasonal operating strategies

b)In New Processes
Design

  1. optimise flowsheet
  2. optimise operation economically
  3. optimise unit
  4. determine process sensitivities
Evaluation
  1. predict effect on whole system
  2. aid feasibility studies
  3. guide scale-up
  4. evaluate alternatives
  5. estimate possible effluents
  6. guide further research
c) Other
  1. equipment design
  2. sensitivity testing
  3. operating strategy evaluation
  4. process and production control
  5. energy conservation
  6. management information
  7. business planning
  8. training and teaching
  9. improve communication, reproducibility and accuracy

Limitations of Process Simulation
The following limitations of process simulation should be recognised by management:

  1. requires discipline with respect to record keeping
  2. high initial training cost
  3. results are only as good as the models and plant data available and hence may be given undue credibility
  4. costly for small, simple, one-time problems
  5. many process units do not have equivalent simulator models
  6. the properties of many substances are not in simulator data banks

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Requirements for Process Simulation


  • process understanding
  • motivated people
  • software
  • computer and peripherals
  • training

Persons skilled in process simulation have to be able to identify the unit operations and the process and information streams linking the unit operations. There are four types of process stream: material, thermal, work and information. There is a need to identify the material streams and identify the physical properties important in those streams and in the unit operations. Simulators have a library of unit operations. The operations of the system need to be matched with those in the library.

Austherm Pty Ltd personnel have the skills and experience to assist your organisation to obtain maximum value from process simulation while avoiding the pitfalls.

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Bibliography


Aris,R., 1994. "Mathematical Modelling Techniques", Dover, New York

Benedek,P., Ed, 1980. "Steady-State Flow-Sheeting of Chemical Plants", Elsevier, Amsterdam

Bequette,B.W., 1998. "Process Dynamics: Modeling, Analysis, and Simulation", Prentice-Hall, Upper Saddle River

Buchanan,J.L. and Turner,P.R., 1988. "Numerical Methods and Analysis", McGraw-Hill, New York

Denn,M., 1986. "Process Modeling", Longman, Harlow

Edgar,T.F. and Himmelblau,D.M., 1988. "Optimization of Chemical Processes", McGraw-Hill, New York

Elimelech,M., Gregory,J., Jia,X. & Williams,R.A., 1995. "Particle Deposition & Aggregation. Measurement, Modelling and Simulation", Butterworth-Heinemann, Woburn

Luyben,W.L., 1974. "Process Modeling, Simulation and Control for Chemical Engineers", McGraw-Hill, Auckland

McConnell,R.R., "A Manager's Guide to Process Simulation", TAPPI Press, Atlanta

Miller,D.M. and Schmidt,J.W., 1984. "Industrial Engineering and Operations Research", Wiley, New York

Papalambros,P.Y. and Wilde,D.J., 1991. "Principles of Optimal Design", Cambridge, Cambridge

Pegden,C.D., Shannon,R.E., & Sadowski,R.P., 1995. "Introduction to Simulation using Siman"", McGraw-Hill, New York

Press,W.H., Flannery,B.P., Teukolsky,S.A. and Vetterling,W.T., 1986, 1992.,"Numerical Recipes" 1st Ed., 2nd Ed., Cambridge, Cambridge

Raman,R., 1985. "Chemical Process Computations", Elsevier, London

Ramirez,W.F., 1989. "Computational Methods for Process Simulation", Butterworths, Boston

Savic,D. & Savic,D., 1989. "BASIC Technical Systems Simulation", Butterworths, London

Slyberg,O., Wild,N.W. & Simons,H.A., 1992. "Introduction to Process Simulation", 2nd Ed., TAPPI Press, Atlanta

Williams,H.P., 1993. ""Model Building in Mathematical Programming", Wiley, Chichester

Zeigler,B.P., 1984. "Theory of Modelling and Simulation", Krieger, Malabar

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