Coarse-grid, filtered, and downsampled flow fields often retain the dominant large-scale organization of a high-fidelity (HF) solution while losing localized gradients, interfaces, shear layers, corner vortices, and curved-wall details. We, therefore, examine cross-fidelity errors from a fluid-mechanics perspective and...
Cheng-Cheng Yang, Hong-Wei Tang, Qing-Feng Wang et al.· The Physics of Fluids· 0 citations
Mesh generation is a critical step in the numerical simulation of computational fluid dynamics, with mesh quality directly affecting both computational efficiency and result accuracy. Traditional methods for mesh topology generation heavily rely on human expertise and heuristic algorithms, often lacking a rigorous math...
Miao-Miao Sun, Fa-Zhi Tang, Yu-Bo Li et al.· The Physics of Fluids· 0 citations
As nonlinearity strengthens, the accuracy advantage of discretization-based constraints becomes increasingly pronounced, with smaller optimization errors compensating for the truncation errors, and the more complex the nonlinearity and boundary conditions, the greater the advantage of GNN over MLP.
Xing Guo, Hong-Wei Tang, Ze-Wei Meng et al.· 0 citations
Experiments show that FC-VPINN achieves approximately one-order-of-magnitude lower prediction errors than the traditional PINN and reduces memory usage to 40% of that required by the baseline, demonstrating improved accuracy and computational efficiency in multidimensional problems.
Wenjie Zhang, Yu-Bo Li, Wei-Dong Cui et al.· Chinese Physics B· 0 citations
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