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An intelligent modelling interface for process simulators in process industries

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thesis
posted on 07.12.2010, 11:36 authored by Graham A. Clark
Over the past three decades, modelling packages for chemical processes have become more advanced and widely used. For example, equation-oriented dynamic simulators, such as gPROMS are useful for simulating plantwide processes as well as unit operations, and are widely used by process engineers. Whereas, other types of simulator (e.g. Simulink) are often used by control engineers to solve complex control problems. However, both these types of simulator rely on the user being proficient in modelling and familiar with their syntax beforehand. A useful development would be the integration of some knowledge into the formation of the process models and automatic syntax code generation. This would lead to the design engineers having a library of knowledge to check on first, much as an expert engineer uses their past experiences to help guide them through a design. If this could be incorporated into a modelling interface this would greatly help the design engineer, especially when tackling problems in areas that they have little, or no experience. The thesis addresses this problem and describes the design of an intelligent modelling interface that incorporates a knowledge base using some form of a priori case library and recall facility. The interface also incorporates an automatic input file generation stage. At present, the user can: specify a single unit operation problem to search for, retrieve similar cases from the database, specify their solution in the database based on past cases and experience, and then automatically generate an input file for either gPROMS or Simulink. These features are demonstrated through four case studies.

History

School

  • Science

Department

  • Computer Science

Publisher

© Graham Clark

Publication date

2001

Notes

A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.

EThOS Persistent ID

uk.bl.ethos.394912

Language

en