Two new variational multiscale evolve-filter algorithms recover vortex shedding in under-resolved cylinder flow simulations at Re=1000, in both full-order and reduced-order settings.
Residual Data-Driven Variational Multiscale Reduced Order Models for Parameter Dependent Problems
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abstract
In this paper, we investigate the modeling of sub-scale components of proper orthogonal decomposition reduced order models (POD-ROMs) of convection-dominated flows. We propose ROM closure models that depend on the ROM residual. We illustrate the new residual-based data-driven ROM closure within the variational multiscale (VMS) framework and investigate it in the numerical simulation of a one-dimensional parameter-dependent convection-dominated convection-diffusion problem. For comparison purposes, we also investigate a streamline-upwind Petrov-Galerkin (SUPG) ROM stabilization strategy and the standard Galerkin ROM (G-ROM). Our numerical investigation shows that the new residual-based data-driven VMS-ROM is more accurate than both the standard G-ROM and the SUPG-ROM.
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math.NA 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
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Variational Multiscale Evolve and Filter Strategies for Convection-Dominated Flows
Two new variational multiscale evolve-filter algorithms recover vortex shedding in under-resolved cylinder flow simulations at Re=1000, in both full-order and reduced-order settings.