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.

中文翻译：

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基于单元平滑有限元模型的 RANS 湍流模型评估，用于预测湍流


越来越多的文献认识到平滑有限元法 (S-FEM) 在计算流体动力学 (CFD) 领域以及在较小程度上在复杂湍流问题中的重要性。本研究评估了 S-FEM 框架内雷诺平均纳维-斯托克斯 (RANS) 湍流模型的性能，用于预测不可压缩湍流。我们对基于单元的 S-FEM (CS-FEM) 的三种湍流模型的评估得到了对三个流动问题的测试的有力支持。研究发现，与有限体积法（FVM）相比，CS-FEM 表现出优异的网格鲁棒性，并且比有限元法（FEM）具有更高的计算精度。值得注意的是，CS-FEM 与标准 k-epsilon 模型 (CS-FEM-SKE) 和可实现的 k-epsilon 模型 (CS-FEM-RKE) 相结合，在处理严重扭曲的网格方面表现出强大的性能，其中 CS-FEM-RKE在强流动分离和对流区域表现出色。采用 CS-FEM (CS-FEM-SA) 的 Spalart-Allmaras 模型提供更快的计算速度，但网格鲁棒性较差。采用基于CS-FEM-RKE的六核网格来评估高速列车（HST）的空气动力学性能，从而提高了计算效率。结果与其他数值研究和实验数据显示出良好的一致性。总体而言，它也凸显了CS-FEM在解决复杂工程问题方面的潜在能力。