Automatic generation of pipelines into a 3D industrial process model

Seppo A. Sierla, Tommi A. Karhela, Valeriy Vyatkin

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)

Abstract

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, firstprinciples 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 3D 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 3D models based on machine-readable P&ID information. The main focus of the algorithm is the automatic generation of feasible pipelines into the 3D models, so that the model has sufficient information which can be exploited in further work to automatically generate high fidelity first-principles thermohydraulic simulations.

Original languageEnglish
Article number8114174
Pages (from-to)26591-26603
Number of pages13
JournalIEEE Access
Volume5
DOIs
Publication statusPublished - 2017
MoE publication typeA1 Journal article-refereed

    Fingerprint

Keywords

  • Buildings
  • Control systems
  • Development lifecycle
  • First-principle model
  • Industrial plants
  • Model generation
  • Pipelines
  • Simulation
  • Solid modeling
  • Three-dimensional displays

Cite this

Sierla, S. A., Karhela, T. A., & Vyatkin, V. (2017). Automatic generation of pipelines into a 3D industrial process model. IEEE Access, 5, 26591-26603. [8114174]. https://doi.org/10.1109/ACCESS.2017.2774835