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Reduced basis methods are popular for approximately solving large and complex systems of differential equations. However, conventional reduced basis methods do not generally preserve conservation laws and symmetries of the full order model.…

Numerical Analysis · Mathematics 2018-03-20 Babak Maboudi Afkham , Jan S. Hesthaven

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

We introduce a filtering technique for Discontinuous Galerkin approximations of hyperbolic problems. Following an approach already proposed for the Hamilton-Jacobi equations by other authors, we aim at reducing the spurious oscillations…

Numerical Analysis · Mathematics 2023-05-18 Giuseppe Orlando

We propose a novel model reduction approach for the approximation of non linear hyperbolic equations in the scalar and the system cases. The approach relies on an offline computation of a dictionary of solutions together with an online…

Numerical Analysis · Mathematics 2016-03-09 Remi Abgrall , David Amsallem , Roxana Crisonovan

This work proposes novel techniques for the efficient numerical simulation of parameterized, unsteady partial differential equations. Projection-based reduced order models (ROMs) such as the reduced basis method employ a (Petrov-)Galerkin…

Numerical Analysis · Mathematics 2023-12-05 Nicholas Mueller , Santiago Badia

The ab initio description of the spectral interior of the absorption spectrum poses both a theoretical and computational challenge for modern electronic structure theory. Due to the often spectrally dense character of this domain in the…

Computational Engineering, Finance, and Science · Computer Science 2019-03-21 Roel Van Beeumen , David B. Williams-Young , Joseph M. Kasper , Chao Yang , Esmond G. Ng , Xiaosong Li

Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems. This paper applies machine learning techniques to improve…

Machine Learning · Computer Science 2015-11-11 Azam Moosavi , Razvan Stefanescu , Adrian Sandu

We develop high-order numerical schemes to solve random hyperbolic conservation laws using linear programming. The proposed schemes are high-order extensions of the existing first-order scheme introduced in [{\sc S. Chu, M. Herty, M.…

Numerical Analysis · Mathematics 2025-09-03 Shaoshuai Chu , Michael Herty

We study the well-posedness of the Bayesian inverse problem for scalar hyperbolic conservation laws where the statistical information about inputs such as the initial datum and (possibly discontinuous) flux function are inferred from noisy…

Numerical Analysis · Mathematics 2021-07-23 Siddhartha Mishra , David Ochsner , Adrian M. Ruf , Franziska Weber

Geophysical flow simulations using hyperbolic shallow water moment equations require an efficient discretization of a potentially large system of PDEs, the so-called moment system. This calls for tailored model order reduction techniques…

Numerical Analysis · Mathematics 2024-07-17 Julian Koellermeier , Philipp Krah , Jonas Kusch

In this article we are interested in the boundary stabilization in finite time of one-dimensional linear hyperbolic balance laws with coefficients depending on time and space. We extend the so called "backstepping method" by introducing…

Optimization and Control · Mathematics 2020-11-30 Jean-Michel Coron , Long Hu , Guillaume Olive , Peipei Shang

In this work we explore the fidelity of numerical approximations to the analytic spectra of hyperbolic partial differential equation systems with variable coefficients. We are particularly interested in the ability of discrete methods to…

Numerical Analysis · Mathematics 2025-08-12 Brittany A. Erickson

This paper presents a backstepping approach for the boundary control of first-order hyperbolic equations with spatially varying coefficients posed on domains of arbitrary dimension. The method is based on a change of variables induced by…

Systems and Control · Electrical Eng. & Systems 2026-05-26 Mohamed Camil Belhadjoudja

In this paper we extend the hierarchical model reduction framework based on reduced basis techniques for the application to nonlinear partial differential equations. The major new ingredient to accomplish this goal is the introduction of…

Numerical Analysis · Mathematics 2017-02-27 Kathrin Smetana , Mario Ohlberger

In this paper, we develop bound-preserving (BP) finite-volume schemes for hyperbolic conservation laws on adaptive moving meshes. For scalar conservative laws, we rewrite the conventional high-order discretization as a convex combination of…

Numerical Analysis · Mathematics 2026-02-16 Yaguang Gu , Guanghui Hu , Tao Tang

Reduced order models of nonlinear conservation laws in fluid dynamics do not typically inherit stability properties of the full order model. We introduce projection-based hyper-reduced models of nonlinear conservation laws which are…

Numerical Analysis · Mathematics 2020-10-28 Jesse Chan

We consider solutions of hyperbolic conservation laws regularized with vanishing diffusion and dispersion terms. Following a pioneering work by Schonbek, we establish the convergence of the regularized solutions toward discontinuous…

Analysis of PDEs · Mathematics 2007-12-04 Cezar Kondo , Philippe G. LeFloch

We introduce novel approximate systems for dispersive and diffusive-dispersive equations with nonlinear fluxes. For purely dispersive equations, we construct a first-order, strictly hyperbolic approximation. Local well-posedness of smooth…

Analysis of PDEs · Mathematics 2025-12-05 Rahul Barthwal , Firas Dhaouadi , Christian Rohde

Directional interpolation is a fast and efficient compression technique for high-frequency Helmholtz boundary integral equations, but it requires a very large amount of storage in its original form. Algebraic recompression can significantly…

Numerical Analysis · Mathematics 2023-10-23 Steffen Börm , Janne Henningsen

In this contribution we investigate in mathematical modeling and efficient simulation of biological cells with a particular emphasis on effective modeling of structural properties that originate from active forces generated from…

Numerical Analysis · Mathematics 2021-11-02 Tobias Leibner , Maja Matis , Mario Ohlberger , Stephan Rave