论文标题
混合数据驱动的闭合策略，用于减少订单建模
Hybrid Data-Driven Closure Strategies for Reduced Order Modeling
论文作者
论文摘要
在本文中，我们提出了用于流体流的混合数据驱动的ROM关闭。这些新的ROM封闭结合了两种根本不同的策略：（i）纯粹的数据驱动的ROM封闭，无论是出于速度和压力而言； （ii）基于物理的，涡流数据驱动的封闭，对系统中的能量转移进行了建模。第一个策略在于将闭合/更正术语添加到管理方程式中，这是根据可用数据构建的。第二种策略包括通过添加涡流粘度项来建模，这些粘度术语是通过使用机器学习技术确定的。本文首次合并了两种策略，以调查在RE = 50000处经过圆形圆柱体的二维流。我们的数值结果表明，混合数据驱动的ROM比纯数据驱动的ROM和EDDY粘度ROM更准确。
In this paper, we propose hybrid data-driven ROM closures for fluid flows. These new ROM closures combine two fundamentally different strategies: (i) purely data-driven ROM closures, both for the velocity and the pressure; and (ii) physically based, eddy viscosity data-driven closures, which model the energy transfer in the system. The first strategy consists in the addition of closure/correction terms to the governing equations, which are built from the available data. The second strategy includes turbulence modeling by adding eddy viscosity terms, which are determined by using machine learning techniques. The two strategies are combined for the first time in this paper to investigate a two-dimensional flow past a circular cylinder at Re=50000. Our numerical results show that the hybrid data-driven ROM is more accurate than both the purely data-driven ROM and the eddy viscosity ROM.
