Work

MOR-TL: A novel model order reduction method for parametrized problems with application to seismic wave propagation

Year: 2026

Type: article

Abstract: This paper presents an efficient strategy for constructing Reduced-Order Model (ROM) bases using Taylor polynomial expansions and Fréchet derivatives with respect to model parameters. The proposed approach enables the construction of ROM bases with minimal additional computational cost. By exploiting Fréchet derivatives – solution to the same problem with distinct right-hand sides – the method introduces a streamlined multiple-right-hand-side (RHS) strategy for ROM bases construction. This approach not only reduces overall computational expenses but also improves accuracy during model parameter updates. Numerical experiments on a two-dimensional wave problem demonstrate significant efficiency gains and enhanced performance, highlighting the potential of the proposed method to advance computational cost-effectiveness, particularly in seismic inversion applications.

Source: Journal of Computational and Applied Mathematics

DOI: 10.1016/j.cam.2026.118249

Authors: Julien Besset, Hélène Barucq, Rabia Djellouli, Stefano Frambati

Institutions: Université de Pau et des Pays de l'Adour, California State University, Northridge

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,250

OpenAlex ID: W4410101228

FWCI:

Cites: 30

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Related to: 10