Automatic Generation of a High-Fidelity Dynamic Thermal-hydraulic Process Simulation Model from a 3D Plant Model

Tutkimustuotos: Lehtiartikkeli

Tutkijat

Organisaatiot

  • VTT Technical Research Centre of Finland
  • Luleå University of Technology

Kuvaus

Dynamic thermal-hydraulic simulation models have been extensively used by process industry for decision support in sectors such as power generation, mineral processing, pulp and paper, and oil and gas. Ever-growing competitiveness in the process industry forces experts to rely even more on dynamic simulation results to take decisions across the process plant lifecycle. However, time-consuming development of simulation models increases model generation costs, limiting their use in a wider number of applications. Detailed 3D plant models, developed during early plant engineering for process design, could potentially be used as a source of information to enable rapid development of high-fidelity simulation models. This paper presents a method for automatic generation of a thermal-hydraulic process simulation model from a 3D plant model. Process structure, dimensioning and component connection information included in the 3D plant model is extracted from the machine-readable export of the 3D design tool and used to automatically generate and configure a dynamic thermal-hydraulic simulation model. In particular, information about the piping dimensions and elevations is retrieved from the 3D plant model and used to calculate head loss coefficients of the pipelines and to configure the piping network model. This step, not considered in previous studies, is crucial for obtaining high-fidelity industrial process models. The proposed method is tested using a laboratory process and the results of the automatically generated model are compared with experimental data from the physical system as well as with a simulation model developed using design data utilized by existing methods on the state-of-the-art. Results show that the proposed method is able to generate high-fidelity models which are able to accurately predict the targeted system, even during operational transients.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut45217-45232
Sivumäärä16
JulkaisuIEEE Access
Vuosikerta6
TilaJulkaistu - 13 elokuuta 2018
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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