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The purpose of this work is to present a reduced order modeling framework for parametrized turbulent flows with moderately high Reynolds numbers within the variational multiscale (VMS) method. The Reduced Order Models (ROMs) presented in…

Numerical Analysis · Mathematics 2023-08-08 Giovanni Stabile , Francesco Ballarin , Giacomo Zuccarino , Gianluigi Rozza

A Finite-Volume based POD-Galerkin reduced order modeling strategy for steady-state Reynolds averaged Navier--Stokes (RANS) simulation is extended for low-Prandtl number flow. The reduced order model is based on a full order model for which…

Fluid Dynamics · Physics 2020-08-04 Kelbij Star , Giovanni Stabile , Gianluigi Rozza , Joris Degroote

In the literature on projection-based nonlinear model order reduction for fluid dynamics problems, it is often claimed that due to modal truncation, a projection-based reduced-order model (PROM) does not resolve the dissipative regime of…

Numerical Analysis · Mathematics 2020-08-10 Sebastian Grimberg , Charbel Farhat , Noah Youkilis

Estimating the temperature field of a building envelope could be a time-consuming task. The use of a reduced-order method is then proposed: the Proper Generalized Decomposition method. The solution of the transient heat equation is then…

Computational Engineering, Finance, and Science · Computer Science 2021-11-18 Marie-Hélène Azam , Julien Berger , Sihem Guernouti , Philippe Poullain , Marjorie Musy

In this work we propose tailored model order reduction for varying boundary optimal control problems governed by parametric partial differential equations. With varying boundary control, we mean that a specific parameter changes where the…

Numerical Analysis · Mathematics 2024-01-22 Maria Strazzullo , Fabio Vicini

The impact of chemical reactions on the robustness and accuracy of projection-based Reduced-Order Models (ROMs) of fluid flows is investigated. Both Galerkin and Least-Squares Petrov Galerkin ROMs are shown to be less robust in reacting…

Computational Physics · Physics 2019-07-19 Cheng Huang , Karthik Duraisamy , Charles L. Merkle

Vortex shedding around circular cylinders is a well known and studied phenomenon that appears in many engineering fields. A Reduced Order Model (ROM) of the incompressible flow around a circular cylinder is presented in this work. The ROM…

Numerical Analysis · Mathematics 2018-02-06 Giovanni Stabile , Saddam Hijazi , Andrea Mola , Stefano Lorenzi , Gianluigi Rozza

An analysis of calibration for reduced-order models (ROMs) is presented in this work. The Galerkin and least-squares Petrov-Galerkin (LSPG) methods are tested on compressible flows involving a disparity of temporal scales. A novel…

Computational Physics · Physics 2021-03-17 Victor Zucatti , William R. Wolf , Michel Bergmann

This paper explores an iterative coupling approach to solve linear thermo-poroelasticity problems, with its application as a high-fidelity discretization utilizing finite elements during the training of projection-based reduced order…

Numerical Analysis · Mathematics 2024-01-08 Francesco Ballarin , Sanghyun Lee , Son-Young Yi

Within the environmental context, numerical modeling is a promising approach to assessing the energy efficiency of buildings. Resilient buildings need to be designed, and capable of adapting to future extreme heat. Simulations are required…

Computational Engineering, Finance, and Science · Computer Science 2022-06-20 Julien Berger , Cyrille Allery , Anaïs Machard

We present and analyze a discontinuous Galerkin method for the numerical modelling of the non-linear fully-coupled thermo-poroelastic problem. For the spatial discretization, we design a high-order discontinuous Galerkin method on polygonal…

Numerical Analysis · Mathematics 2022-05-27 Paola F. Antonietti , Stefano Bonetti , Michele Botti

For over a century, reduced order models (ROMs) have been a fundamental discipline of theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr-Sommerfeld stability equation and numerous vortex models, of which…

Fluid Dynamics · Physics 2021-10-04 Shady E. Ahmed , Suraj Pawar , Omer San , Adil Rasheed , Traian Iliescu , Bernd R. Noack

We present a partitioned Model Order Reduction method for multiphysics problems, that is based on a semi-implicit treatment of the coupling conditions, and on a projection scheme. The proposed Reduced Order Method is based on the Proper…

Numerical Analysis · Mathematics 2023-08-08 Monica Nonino , Francesco Ballarin , Gianluigi Rozza , Yvon Maday

In this paper, a stabilized proper orthogonal decomposition (POD) reduced-order model (ROM) is presented for the barotropic vorticity equation. We apply the POD-ROM model to mid-latitude simplified oceanic basins, which are standard…

Fluid Dynamics · Physics 2018-01-29 Omer San , Traian Iliescu

We present a reduced order method (ROM) based on proper orthogonal decomposition (POD) for the viscous Burgers' equation and the incompressible Navier-Stokes equations discretized using an implicit-explicit hybrid discontinuous…

Numerical Analysis · Mathematics 2020-04-21 Guosheng Fu , Zhu Wang

This study concerns the development of a data-based compact model for the prediction of the fluid temperature evolution in district heating (DH) pipeline networks. This so-called "reduced-order model" (ROM) is obtained from reduction of the…

Numerical Analysis · Mathematics 2022-11-28 Mengting Jiang , Michel Speetjens , Camilo Rindt , David Smeulders

In this work, we present an approach for the efficient treatment of parametrized geometries in the context of POD-Galerkin reduced order methods based on Finite Volume full order approximations. On the contrary to what is normally done in…

Numerical Analysis · Mathematics 2020-02-07 Giovanni Stabile , Matteo Zancanaro , Gianluigi Rozza

In this work, we develop a novel Galerkin-L1-POD scheme for the subdiffusion model with a Caputo fractional derivative of order $\alpha\in (0,1)$ in time, which is often used to describe anomalous diffusion processes in heterogeneous media.…

Numerical Analysis · Mathematics 2016-02-02 Bangti Jin , Zhi Zhou

Galerkin-based reduced-order models (G-ROMs) offer efficient and accurate approximations for laminar flows but require hundreds to thousands of modes $N$ to capture the complex dynamics of turbulent flows. This makes standard G-ROMs…

Fluid Dynamics · Physics 2025-06-11 Ping-Hsuan Tsai , Paul Fischer , Edgar Solomonik

Model-reduction techniques aim to reduce the computational complexity of simulating dynamical systems by applying a (Petrov-)Galerkin projection process that enforces the dynamics to evolve in a low-dimensional subspace of the original…

Computational Engineering, Finance, and Science · Computer Science 2021-04-02 A. Schein , K. T. Carlberg , M. J. Zahr