Pressure Data-Driven Variational Multiscale Reduced Order Models

Ivagnes, Anna; Stabile, Giovanni; Mola, Andrea; Iliescu, Traian; Rozza, Gianluigi

doi:10.48550/arxiv.2205.15118

Cited by 2 publications

(14 citation statements)

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“…The ROM construction uses the following different stabilization approaches for the velocitypressure coupling [23]:…”

Section: The Pod-galerkin Romsmentioning

confidence: 99%

“…We consider the data-driven variational multiscale ROM (DD-VMS-ROM ) framework [23], in which different correction/closure terms are introduced in the formulations of SUP-ROM(8) and PPE-ROM (9). The DD-VMS-SUP-ROM approach (section 4.1) includes only velocity correction terms, whereas the DD-VMS-PPE-ROM approach (section 4.2) includes both pressure and velocity correction terms.…”

Section: Data-driven Vms-romsmentioning

confidence: 99%

“…The terms τ u and τ p are evaluated by solving a least square problem that minimizes the difference between the model form of the correction terms and the exact correction terms, which are evaluated by using the available FOM data [23,57,34,36]. The technique used to compute the correction terms takes inspiration from the operator inference approach [41,29,8,27].…”

Section: Introductionmentioning

confidence: 99%

“…The technique used to compute the correction terms takes inspiration from the operator inference approach [41,29,8,27]. In [23], the purely datadriven approach was applied for the first time to the pressure Poisson formulation (PPE-ROM), leading to the introduction of the novel pressure correction term, τ p . This strategy has significantly increased the accuracy of the pressure field approximation.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, the new hybrid data-driven ROM (4) is compared to (i) the purely data-driven ROM (2) proposed in [23], and (ii) the physically-based data-driven ROM (3) proposed in [18]. The three ROMs are tested and compared on the classical case study of a turbulent flow around a cylinder.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Hybrid Data-Driven Closure Strategies for Reduced Order Modeling

Ivagnes¹,

Stabile²,

Mola³

et al. 2022

Preprint

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In this paper, we propose hybrid data-driven ROM closures for fluid flows. These new ROM closures combine two fundamentally different strategies: (i) purely data-driven ROM closures, both for the velocity and the pressure; and (ii) physically based, eddy viscosity data-driven closures, which model the energy transfer in the system. The first strategy consists in the addition of closure/correction terms to the governing equations, which are built from the available data. The second strategy includes turbulence modeling by adding eddy viscosity terms, which are determined by using machine learning techniques. The two strategies are combined for the first time in this paper to investigate a two-dimensional flow past a circular cylinder at Re " 50 000. Our numerical results show that the hybrid data-driven ROM is more accurate than both the purely data-driven ROM and the eddy viscosity ROM.

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“…The ROM construction uses the following different stabilization approaches for the velocitypressure coupling [23]:…”

Section: The Pod-galerkin Romsmentioning

confidence: 99%

Section: Data-driven Vms-romsmentioning

confidence: 99%