A Reduced Basis Technique for Long-Time Unsteady Turbulent Flows
Lambert Fick, Yvon Maday, Anthony T Patera, Tommaso Taddei

TL;DR
This paper introduces a novel reduced basis method for long-time simulation of parametrized turbulent flows, incorporating a constrained formulation, an efficient error indicator, and a Greedy algorithm for parameter space coverage.
Contribution
The paper presents a constrained Galerkin formulation, an posteriori error indicator, and a Greedy algorithm for efficient reduced basis construction in turbulent flow simulations.
Findings
Effective reduced basis for long-time turbulent flow simulation
Error indicator correlates with mean flow prediction accuracy
Method demonstrates strong performance on lid-driven cavity flow
Abstract
We present a reduced basis technique for long-time integration of parametrized incompressible turbulent flows. The new contributions are threefold. First, we propose a constrained Galerkin formulation that corrects the standard Galerkin statement by incorporating prior information about the long-time attractor. For explicit and semi-implicit time discretizations, our statement reads as a constrained quadratic programming problem where the objective function is the Euclidean norm of the error in the reduced Galerkin (algebraic) formulation, while the constraints correspond to bounds for the maximum and minimum value of the coefficients of the -term expansion. Second, we propose an \emph{a posteriori} error indicator, which corresponds to the dual norm of the residual associated with the time-averaged momentum equation. We demonstrate that the error indicator is highly-correlated with…
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Taxonomy
TopicsModel Reduction and Neural Networks · Numerical methods for differential equations · Advanced Numerical Methods in Computational Mathematics
