论文标题
LES滤波方法的POD-Galerkin降低订购模型
A POD-Galerkin reduced order model for a LES filtering approach
论文作者
论文摘要
我们为LERAY模型提出了适当的正交分解（POD） - 基林的降低订单模型（ROM）。对于模型的实现，我们将一种称为Evolve-Filter（EF）的两步算法与计算有效的有限体积方法相结合。所提出的方法的主要新颖性依赖于将空间滤波施加到收集快照和减少的订单模型中，以及考虑在降低水平下的压力场。在EF算法的两个步骤中，使用不同的POD基础和系数近似速度和压力场。为了重建压力场，我们使用压力泊松方程方法。我们在两个基准问题上测试ROM：在雷诺数0 <= re <= 100处的圆柱体上的2D和3D不稳定流量。降低订单模型的准确性是根据完整阶模型获得的结果评估的。对于2D情况，还提出了有关滤波半径的参数研究。
We propose a Proper Orthogonal Decomposition (POD)-Galerkin based Reduced Order Model (ROM) for a Leray model. For the implementation of the model, we combine a two-step algorithm called Evolve-Filter (EF) with a computationally efficient finite volume method. The main novelty of the proposed approach relies in applying spatial filtering both for the collection of the snapshots and in the reduced order model, as well as in considering the pressure field at reduced level. In both steps of the EF algorithm, velocity and pressure fields are approximated by using different POD basis and coefficients. For the reconstruction of the pressures fields, we use a pressure Poisson equation approach. We test our ROM on two benchmark problems: 2D and 3D unsteady flow past a cylinder at Reynolds number 0 <= Re <= 100. The accuracy of the reduced order model is assessed against results obtained with the full order model. For the 2D case, a parametric study with respect to the filtering radius is also presented.
