Validation of a functional model for integration of safety into process system design

Jing Wu, M. Lind, X. Zhang, S. B. Jørgensen, G. Sin

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Qualitative modeling paradigm offers process systems engineering a potential for developing effective tools for handling issues related to Process Safety. A qualitative functional modeling environment can accommodate different levels of abstraction for capturing knowledge associated with the process system functionalities as required for the intended safety applications. To provide the scientific rigor and facilitate the acceptance of qualitative modelling, this contribution focuses on developing a scientifically based validation method for functional models. The Multilevel Flow Modeling (MFM) methodology is adopted in the paper as a formalized qualitative functional modeling methodology for dynamic process systems. A functional model validation procedure is proposed to assess whether the intended modeling purpose indeed represents a relevant proposal and whether the model represents the system behavior sufficiently well. With the reasoning capability provided by the MFM syntax and semantics, the validation procedure is illustrated on a three-phase separator system of an MFM model. The MFM model reasoning results successfully compares against analysis results from API RP. 14-C.
Original languageEnglish
Title of host publicationProceedings of the 25th European Symposium on Computer Aided Process Engineering
EditorsKrist V. Gernaey, Jakob K. Huusom, Rafiqul Gani
Publication date2015
Publication statusPublished - 2015
Event25th European Symposium on Computer Aided Process Engineering : 12th International Symposium on Process Systems Engineering - Copenhagen, Denmark
Duration: 31 May 20154 Jun 2015


Conference25th European Symposium on Computer Aided Process Engineering
Internet address
SeriesComputer Aided Chemical Engineering


  • Functional Model
  • Multilevel Flow Modeling
  • Model Validation
  • Process Safety


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