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Automatic Generation of Pipelines Into a 3D Industrial Process Model
Department of Electrical Engineering and Automation, Aalto University.
Department of Electrical Engineering and Automation, Aalto University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.ORCID iD: 0000-0002-9315-9920
2017 (English)In: IEEE Access, ISSN 2169-3536, Vol. 5, p. 26591-26603Article in journal (Refereed) Published
Abstract [en]

Simulation has become an established technique to support the design of complex, mechatronic or cyber-physical systems. Ideally, simulations should already be performed at an early design phase before high-cost design commitments are made, and the recent advances in the digitalization of design information open possibilities for automatic generation of simulation models. However, high-fidelity simulation model building depends on accurate data. In particular, first-principles models are desirable source information for simulations, but such models generally are not available at an early design stage. This paper investigates the automatic generation of first-principles 3-D models for piping intensive systems based on design information that is available at an early design stage, namely piping & instrumentation diagrams (P&ID). An algorithm is presented for the generation of such 3-D models based on machine-readable P&ID information. The main focus of the algorithm is the automatic generation of feasible pipelines into the 3-D models, so that the model has sufficient information, which can be exploited in further work to automatically generate high fidelity first-principles thermo-hydraulic simulations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. Vol. 5, p. 26591-26603
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-67381DOI: 10.1109/ACCESS.2017.2774835ISI: 000418881100044OAI: oai:DiVA.org:ltu-67381DiVA, id: diva2:1177067
Note

Validerad;2018;Nivå 2;2018-01-24 (andbra)

Available from: 2018-01-24 Created: 2018-01-24 Last updated: 2018-01-24Bibliographically approved

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CiteExportLink to record
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  • apa
  • harvard1
  • ieee
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  • de-DE
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  • en-US
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  • nn-NO
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  • Other locale
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Output format
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