Data-driven Hi2Lo for Coarse-grid System Thermal Hydraulic Modeling

Arsen S. Iskhakov, Nam T. Dinh, Victor Coppo Leite, Elia Merzari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Traditional 1D system thermal hydraulic analysis has been widely applied in nuclear industry for licensing purposes due to its numerical efficiency. However, such codes are inherently deficient for modeling of multiscale multidimensional flows. For such scenarios coarse-grid 3D simulations are useful due to the balance between the cost and the amount of information a modeler can extract from the results. At the same time, coarse grids do not allow to accurately resolve and capture turbulent mixing in reactor enclosures, while existing turbulence models (closures for the Reynolds stresses or turbulent viscosity) have large model form uncertainties. Thus, there is an interest in the improvement of such solvers. In this work two data-driven high-to-low methodologies to reduce mesh and model-induced errors are explored using a case study based on the Texas A&M upper plenum of high-temperature gas-cooled reactor facility. The first approach relies on the usage of turbulence closure for eddy viscosity with higher resolution/fidelity in a coarse grid solver. The second methodology employs artificial neural networks to map low-fidelity input features with errors in quantities of interest (velocity fields). Both methods have shown potential to improve the coarse grid simulation results by using data with higher fidelity (Reynolds-averaged Navier-Stokes and large eddy simulations), though, influence of the mesh-induced (discretization) error is quite complex and requires further investigations.

Original languageEnglish (US)
Title of host publicationProceedings of Advances in Thermal Hydraulics, ATH 2022 - Embedded with the 2022 ANS Annual Meeting
PublisherAmerican Nuclear Society
Pages403-416
Number of pages14
ISBN (Electronic)9780894487811
DOIs
StatePublished - 2022
Event5th International Topical Meeting on Advances in Thermal Hydraulics 2022, ATH 2022, held in conjunction with the 2022 American Nuclear Society ,ANS Annual Meeting - Anaheim, United States
Duration: Jun 12 2022Jun 16 2022

Publication series

NameProceedings of Advances in Thermal Hydraulics, ATH 2022 - Embedded with the 2022 ANS Annual Meeting

Conference

Conference5th International Topical Meeting on Advances in Thermal Hydraulics 2022, ATH 2022, held in conjunction with the 2022 American Nuclear Society ,ANS Annual Meeting
Country/TerritoryUnited States
CityAnaheim
Period6/12/226/16/22

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Nuclear Energy and Engineering
  • Nuclear and High Energy Physics

Fingerprint

Dive into the research topics of 'Data-driven Hi2Lo for Coarse-grid System Thermal Hydraulic Modeling'. Together they form a unique fingerprint.

Cite this