English(EN) CFD-driven symbolic regression of RANS transition models

CFD驱动的符号回归增强了RANS转捩模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 14:34

研究人员开发了一个CFD驱动的稀疏符号回归框架，为雷诺平均纳维-斯托克斯（RANS）转捩模型创建更准确、更具可解释性的修正。这种新方法利用梯度无关优化和代理模型，识别出间歇方程中激活函数的闭式修正，使用基于局部流动特征的多项式和指数项组合。与传统的调优方法相比，该框架识别出的修正项集更简洁，同时在训练数据和未见过的数据上保持或提高了准确性。 AI

影响这项研究可能带来更准确的流体动力学模拟，影响依赖CFD进行设计和分析的领域。

排序理由该条目描述了一篇关于改进CFD模型新方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-11-02 14:34

CFD驱动的RANS转捩模型符号回归

Laminar-turbulent transition governs skin friction, heat transfer and losses in turbomachinery, yet Reynolds-averaged Navier-Stokes (RANS) transition models rely on empirical correlations and hand-calibrated activation functions whose structural deficiencies cannot be resolved by…

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CFD驱动的RANS转捩模型符号回归

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