A Leray regularized ensemble-proper orthogonal decomposition method for parameterized convection-dominated flows
Max Gunzburger, Traian Iliescu, and Michael Schneier

TL;DR
This paper introduces a Leray regularized ensemble-POD method with spatial filtering to improve the accuracy and stability of reduced order models for convection-dominated flows governed by Navier-Stokes equations, especially in uncertain parameter scenarios.
Contribution
The work presents a novel Leray ensemble-POD model with spatial filtering and a new stable numerical discretization for variable viscosity, enhancing simulation accuracy and stability for convection-dominated flows.
Findings
Leray ensemble-POD yields accurate results in convection-dominated flows.
The new discretization significantly improves numerical stability.
Error estimates for the proposed method are established.
Abstract
Partial differential equations (PDEs) are often dependent on input quantities which are inherently uncertain. To quantify this uncertainty, these PDEs must be solved over a large ensemble of parameters. Even for a single realization this can a computationally intensive process. In the case of flows governed by the Navier-Stokes equations, an efficient method has been devised for computing an ensemble of solutions. To further reduce the computational cost of this method, an ensemble proper orthogonal decomposition (POD) method was recently proposed. The main contribution of this work is the introduction of POD spatial filtering for ensemble-POD methods. The POD spatial filter makes possible the construction of the Leray ensemble-POD model, which is a regularized reduced order model for the numerical simulation of convection-dominated flows. The Leray ensemble-POD model employs the POD…
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