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Pressure data-driven variational multiscale reduced order models

delete2023-03-01
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OA
AI
A
Anna Ivagnes
G
Giovanni Stabile
A
Andrea Mola
T
Traian Iliescu
G
Gianluigi Rozza *
DOI:10.1016/j.jcp.2022.111904delete
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Abstract

Abstract

En 中文
In this paper, we develop data-driven closure/correction terms to increase the pressure and velocity accuracy of reduced order models (ROMs) for fluid flows. Specifically, we propose the first pressure-based data-driven variational multiscale ROM, in which we use the available data to construct closure/correction terms for both the momentum equation and the continuity equation. Our numerical investigation of the two-dimensional flow past a circular cylinder at Re = 50,000 in the marginally-resolved regime shows that the novel pressure data-driven variational multiscale ROM yields significantly more accurate velocity and pressure approximations than the standard ROM and, more importantly, than the original data-driven variational multiscale ROM (i.e., without pressure components). In particular, our numerical results show that adding the closure/correction term in the momentum equation significantly improves both the velocity and the pressure approximations, whereas adding the closure/correction term in the continuity equation improves only the pressure approximation. (c) 2022 Elsevier Inc. All rights reserved.
Keywords:
Reduced order modeling
Pressure stabilization
Variational multiscale
Computational fluid dynamics
Closure model
Data driven model reduction
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Journal

Journal of Computational Physics cover
Journal of Computational Physics
IF:
3.8
Papers:
1.5W
Citations:
7.4W

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