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A novel structure-preserving numerical method to solve random hyperbolic systems of conservation laws is presented. The method uses a concept of generalized, measure-valued solutions to random conservation laws. This yields a linear partial…

Numerical Analysis · Mathematics 2025-10-29 Shaoshuai Chu , Michael Herty , Maria Lukacova-Medvidova , Yizhou Zhou

This work investigates the use of sparse polynomial interpolation as a model order reduction method for the incompressible Navier-Stokes equations. Numerical results are presented underscoring the validity of sparse polynomial…

Numerical Analysis · Mathematics 2022-01-11 Martin W. Hess , Gianluigi Rozza

In this paper we analyze the stability of equilibrium manifolds of hyperbolic shallow water moment equations. Shallow water moment equations describe shallow flows for complex velocity profiles which vary in vertical direction and the…

Fluid Dynamics · Physics 2020-11-18 Qian Huang , Julian Koellermeier , Wen-An Yong

In this work a new finite element based Method of Relaxed Streamline Upwinding is proposed to solve hyperbolic conservation laws. Formulation of the proposed scheme is based on relaxation system which replaces hyperbolic conservation laws…

Numerical Analysis · Mathematics 2019-06-05 Ameya D. Jagtap

Hamiltonian Operator Inference has been introduced in [Sharma, H., Wang, Z., Kramer, B., Physica D: Nonlinear Phenomena, 431, p.133122, 2022] to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. This approach…

Numerical Analysis · Mathematics 2024-05-10 Yuwei Geng , Jasdeep Singh , Lili Ju , Boris Kramer , Zhu Wang

Classical model reduction techniques project the governing equations onto linear subspaces of the high-dimensional state-space. For problems with slowly decaying Kolmogorov-n-widths such as certain transport-dominated problems, however,…

Numerical Analysis · Mathematics 2021-12-22 Patrick Buchfink , Silke Glas , Bernard Haasdonk

This work presents a method for constructing online-efficient reduced models of large-scale systems governed by parametrized nonlinear scalar conservation laws. The solution manifolds induced by transport-dominated problems such as…

Numerical Analysis · Mathematics 2021-01-01 Donsub Rim , Benjamin Peherstorfer , Kyle T. Mandli

The investigation of fluid-solid systems is very important in a lot of industrial processes. From a computational point of view, the simulation of such systems is very expensive, especially when a huge number of parametric configurations…

This work proposes a technique for constructing a statistical closure model for reduced-order models (ROMs) applied to stationary systems modeled as parameterized systems of algebraic equations. The proposed technique extends the…

Numerical Analysis · Mathematics 2024-12-20 Stefano Pagani , Andrea Manzoni , Kevin Carlberg

The shear shallow water model is an extension of the classical shallow water model to include the effects of vertical shear. It is a system of six non-linear hyperbolic PDE with non-conservative products. We develop a high-order entropy…

Numerical Analysis · Mathematics 2023-10-03 Anshu Yadav , Deepak Bhoriya , Harish Kumar , Praveen Chandrashekar

We consider fully discrete embedded finite element approximations for a shallow water hyperbolic problem and its reduced-order model. Our approach is based on a fixed background mesh and an embedded reduced basis. The Shifted Boundary…

Numerical Analysis · Mathematics 2022-06-29 Xianyi Zeng , Giovanni Stabile , Efthymios N. Karatzas , Guglielmo Scovazzi , Gianluigi Rozza

Entropy solutions have been widely accepted as the suitable solution framework for systems of conservation laws in several space dimensions. However, recent results in \cite{CDL1,CDL2} have demonstrated that entropy solutions may not be…

Numerical Analysis · Mathematics 2018-08-01 Ulrik S. Fjordholm , Roger Käppeli , Siddhartha Mishra , Eitan Tadmor

In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework is based on…

Computational Physics · Physics 2020-04-22 Suraj Pawar , Shady E. Ahmed , Omer San , Adil Rasheed

Machine learning and artificial intelligence algorithms typically require large amount of data for training. This means that for nonlinear aeroelastic applications, where small training budgets are driven by the high computational burden…

We develop an optimization-based algorithm for parametric model order reduction (PMOR) of linear time-invariant dynamical systems. Our method aims at minimizing the $\mathcal{H}_\infty \otimes \mathcal{L}_\infty$ approximation error in the…

Systems and Control · Electrical Eng. & Systems 2023-03-21 Paul Schwerdtner , Manuel Schaller

We investigate both theoretically and numerically the consistency between the nonlinear discretization in full order models (FOMs) and reduced order models (ROMs) for incompressible flows. To this end, we consider two cases: (i) FOM-ROM…

Numerical Analysis · Mathematics 2022-09-28 Sean Ingimarson , Leo G. Rebholz , Traian Iliescu

M. Kruskal showed that each nearly-periodic dynamical system admits a formal $U(1)$ symmetry, generated by the so-called roto-rate. We prove that such systems also admit nearly-invariant manifolds of each order, near which rapid…

Dynamical Systems · Mathematics 2021-09-29 J. W. Burby , E. Hirvijoki

This paper investigates some properties of entropy solutions of hyperbolic conservation laws on a Riemannian manifold. First, we generalize the Total Variation Diminishing (TVD) property to manifolds, by deriving conditions on the flux of…

Analysis of PDEs · Mathematics 2007-05-23 Paulo Amorim , Matania Ben-Artzi , Philippe G. LeFloch

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

Multiple model reduction techniques have been proposed to tackle linear and non linear problems. Intrusive model order reduction techniques exhibit high accuracy levels, however, they are rarely used as a standalone industrial tool, because…

Computational Engineering, Finance, and Science · Computer Science 2025-04-10 Mikhael Tannous , Chady Ghnatios , Eivind Fonn , Trond Kvamsdal , Francisco Chinesta
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