A POD-Galerkin reduced order model for a LES filtering approach

JOURNAL OF COMPUTATIONAL PHYSICS

卷:436

Article

Girfoglio, Michele¹  Quaini, Annalisa²  Rozza, Gianluigi¹ 

[1] SISSA, Int Sch Adv Studies, Math Area, mathLab, Via Bonomea 265, I-34136 Trieste, Italy

[2] Univ Houston, Dept Math, Houston, TX 77204 USA

关键词: Proper orthogonal decomposition;    Reduced order model;    Large Eddy Simulation;    Leray model;    Filtering stabilization;    Poisson equation for pressure;   

DOI  :  10.1016/j.jcp.2021.110260

来源: Elsevier

【 摘 要 】

We propose a Proper Orthogonal Decomposition (POD)-Galerkin based Reduced Order Model (ROM) for an implementation of the Leray model that combines 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. (C) 2021 Elsevier Inc. All rights reserved.

【 授权许可】

Free