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Assessment of RANS turbulence models based on the cell-based smoothed finite element model for prediction of turbulent flow.

Authors :
Liu, Mingyang
Jiang, Chen
Gao, Guangjun
Zhu, Huifen
Xu, Lang
Source :
Engineering Analysis with Boundary Elements. Nov2024, Vol. 168, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

• Innovative extension of S-FEM for tackling intricate engineering challenges. • RANS turbulence model assessment in the S-FEM frame for prediction of turbulent flow. • A comparative analysis of the computational accuracy between S-FEM and FVM was conducted, particularly in severely distorted meshes. • Hex-cored mesh based on S-FEM improves turbulent flow analysis efficiency. There is a growing body of literature that recognizes the importance of Smoothed Finite Element Method (S-FEM) in computational fluid dynamics (CFD) fields and, to a lesser extent, in complex turbulent flow problems. This study evaluates the performance of Reynolds-averaged Navier-Stokes (RANS) turbulence models within the S-FEM framework for predicting incompressible turbulent flows. Our assessment of three turbulence models based on the cell-based S-FEM (CS-FEM) is convincingly supported by testing on three flow problems. It is found that the CS-FEM exhibits superior mesh robustness compared to the Finite Volume Method (FVM) and achieves higher computational accuracy than the Finite Element Method (FEM). Notably, the CS-FEM combined with the standard k-epsilon model (CS-FEM-SKE) and the realizable k-epsilon model (CS-FEM-RKE) demonstrate robust performance in handling severely distorted meshes, with CS-FEM-RKE outperforming in regions of strong flow separation and convection. The Spalart-Allmaras model with CS-FEM (CS-FEM-SA) offers faster computational speed but shows poor mesh robustness. The hexcore mesh based on CS-FEM-RKE is employed to evaluate the aerodynamic performance of High-speed train (HST), resulting in enhanced computational efficiency. The outcomes show good agreement with other numerical studies and experimental data. Overall, it also highlights the latent capability of CS-FEM in solving complex engineering problems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09557997
Volume :
168
Database :
Academic Search Index
Journal :
Engineering Analysis with Boundary Elements
Publication Type :
Periodical
Accession number :
179791190
Full Text :
https://doi.org/10.1016/j.enganabound.2024.105937