English(EN) Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics

深度学习模型用于大涡模拟的湍流闭合模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-28 04:00

研究人员开发了一种新的深度学习方法，用于大涡模拟（LES）中的湍流闭合模型。该方法使用一种扰动技术，将直接数值模拟（DNS）数据视为稀疏观测值来训练模型。这允许对闭合模型进行先验训练，使模型能够学习准确统计所需的必要强迫，同时在无需通过 LES 求解器进行反向传播的情况下保持长期稳定性。 AI

影响为模拟中的湍流闭合模型引入了一种更稳定、计算效率更高的方法。

排序理由学术论文，详细介绍了用于湍流建模的新型深度学习方法。

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arXiv cs.LG TIER_1 English(EN) · Ashwin Suriyanarayanan, Melissa Adrian, Dibyajyoti Chakraborty, Romit Maulik · 2026-04-28 04:00

从受扰动 LES 动力学中深度学习求解器感知的湍流闭合模型

arXiv:2604.23874v1 Announce Type: cross Abstract: Deep learning approaches have shown remarkable promise in turbulence closure modeling for large eddy simulations (LES). The differentiable physics paradigm uses the so-called a-posteriori approach for learning by embedding a neura…