High-Fidelity Simulation of Mixing Phenomena in Large Enclosures

Victor Coppo Leite, Elia Merzari, Jiaxin Mao, Victor Petrov, Annalisa Manera

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

In the present work, two large eddy simulations (LESs) of single isothermal jets discharging into large enclosure facilities are proposed. The geometries and tested flow conditions correspond to scaled experiments of the upper plenum of high-temperature gas-cooled reactors. More specifically, two reference experiments were conducted at Texas A&M University and Michigan University. The objective of the present work is to validate these simulations with their corresponding reference experiments. The proposed LES models are performed with NekRS, a spectral element code with graphics processing unit capabilities developed at Argonne National Laboratory. These simulations were performed on the Summit supercomputer at Oak Ridge National Laboratory. For validation purposes, first- and second-order statistics from the computational fluid dynamics (CFD) calculation are compared with measurements obtained from the experiments. The models proved to be accurate, as these results are in good agreement. Additionally, flow visualization is provided showing that these models are able to retrieve similar effects to what are described in the literature for this type of flow configuration. Finally, the proposed models are part of a broader effort under the current Integrated Research Project of Nuclear Energy Advanced Modeling and Simulation 1.1, whose main objective is to deliver fast-running models to accurately predict complex physical phenomena, including for instance, turbulent mixing and thermal stratification. In this regard, the CFD models proposed here will be used to generate a high-fidelity data set to be applied in conjunction with data-driven methods to improve turbulence modeling closures.

Original languageEnglish (US)
JournalNuclear Science and Engineering
DOIs
StateAccepted/In press - 2023

All Science Journal Classification (ASJC) codes

  • Nuclear Energy and Engineering

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