LARGE EDDY SIMULATION OF RANDOM PEBBLE BED USING THE SPECTRAL ELEMENT METHOD

被引:0
|
作者
Tri Nguyen [1 ]
Merzari, Elia [1 ,2 ]
Yuan, Haomin [2 ]
Dai, Dezhi [2 ]
Jackson, Brian [3 ]
机构
[1] Penn State Univ, University Pk, PA 16802 USA
[2] Argonne Natl Lab, Lemont, IL USA
[3] Kairos Power, 707 W Tower Ave, Alameda, CA USA
关键词
LES; FHRs; FLiBE; NekRS; OpenFOAM; PACKED-BEDS; FLOW; HEAT; REACTOR;
D O I
暂无
中图分类号
O414.1 [热力学];
学科分类号
摘要
The evolution of Fluoride-Cooled High-Temperature Reactors (FHRs) that utilize pebble fuel has drastically increased the demand for in-depth understanding of the heat transfer (HT) in packed beds cooled by liquid salts. The complex flow fields found in a pebble bed may require a detailed understanding to ensure the proper cooling of the reactor core during normal and accident conditions. As detailed experimental data is very difficult to obtain for these configurations high fidelity simulation like Large Eddy Simulation (LES) and direct numerical simulation (DNS) can be employed to create a high-resolution HT numerical database that can assist addressing industrial-driven issues associated with the HT behavior of FHRs. In this paper, we performed a series of LES using the GPU-oriented spectral element CFD code NekRS to investigate the HT for a bed of 1741 pebbles at Reynolds numbers ranging from 50 to 1600 based on coolant (FLiBE) inlet velocity. Two different type of pebble power distribution were used, one with the same power density for all pebble, other with different power density. Non conjugate heat transfer (non-CHT) and conjugate heat transfer (CHT) cases have been performed and characteristics of the flow domain such as average, rms, as well as time series of velocity and temperature have been analyzed. The simulation results show a good agreement between non CHT and CHT. In addition, NekRS data have also been compared with OpenFOAM models. The good agreement has also been achieved which gave the confident of the NekRS/OpenFOAM dataset when little to no empirical data is available. The generated data will be used to benchmark HT modeling methods, local maxima/minima of HT parameters and support convective heat transfer quantification for Kairos Power, validating OpenFOAM models, as well as benchmark lower finality models such as Reynolds Averaged Navier Stokes (RANS) and/or porous media approaches.
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页数:12
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