Globalizing manifold-based reduced models for equations and data

Fuente: arXiv
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Auteurs principaux: Kaszás, Bálint, Haller, George
Format: Preprint
Publié: 2025
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author Kaszás, Bálint
Haller, George
author_facet Kaszás, Bálint
Haller, George
contents One of the very few mathematically rigorous nonlinear model reduction methods is the restriction of a dynamical system to a low-dimensional, sufficiently smooth, attracting invariant manifold. Such manifolds are usually found using local polynomial approximations and, hence, are limited by the unknown domains of convergence of their Taylor expansions. To address this limitation, we extend local expansions for invariant manifolds via Padé approximants, which re-express the Taylor expansions as rational functions for broader utility. This approach significantly expands the range of applicability of manifold-reduced models, enabling reduced modeling of global phenomena, such as large-scale oscillations and chaotic attractors of finite element models. We illustrate the power of globalized manifold-based model reduction on several equation-driven and data-driven examples from solid mechanics and fluid mechanics.
format Preprint
id arxiv_https___arxiv_org_abs_2505_05876
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Globalizing manifold-based reduced models for equations and data
Kaszás, Bálint
Haller, George
Dynamical Systems
Chaotic Dynamics
One of the very few mathematically rigorous nonlinear model reduction methods is the restriction of a dynamical system to a low-dimensional, sufficiently smooth, attracting invariant manifold. Such manifolds are usually found using local polynomial approximations and, hence, are limited by the unknown domains of convergence of their Taylor expansions. To address this limitation, we extend local expansions for invariant manifolds via Padé approximants, which re-express the Taylor expansions as rational functions for broader utility. This approach significantly expands the range of applicability of manifold-reduced models, enabling reduced modeling of global phenomena, such as large-scale oscillations and chaotic attractors of finite element models. We illustrate the power of globalized manifold-based model reduction on several equation-driven and data-driven examples from solid mechanics and fluid mechanics.
title Globalizing manifold-based reduced models for equations and data
topic Dynamical Systems
Chaotic Dynamics
url https://arxiv.org/abs/2505.05876