Structure-preserving formulations for data-driven analysis of coupled multi-physics systems

Muixí, Alba ; González, David (Universidad de Zaragoza) ; Chinesta, Francisco ; Cueto, Elías (Universidad de Zaragoza)

Resumen: We develop a novel methodology for data-driven simulation of coupled multi-physics systems. The result of the method is a learned numerical integrator of the coupled system dynamics. In order to preserve the fundamental physics of the coupled systems, and thus preserve the geometrical properties of the governing equations—even if they may be completely unknown—we impose a port-metriplectic structure on the system evolution, i.e., a combination of a symplectic evolution for the system energy with a gradient flow for the entropy of each system, which can be exchanged through predefined ports. The resulting method guarantees by construction the satisfaction of the laws of thermodynamics for open systems, leading to accurate predictions of the future states of their dynamics. Examples are given for systems of varying complexity, based on synthetic as well as experimental data.

Idioma: Inglés

DOI: 10.1007/s00466-024-02508-x

Año: 2025

Publicado en: COMPUTATIONAL MECHANICS 75 (2025), 357–368
ISSN: 0178-7675

Financiación: info:eu-repo/grantAgreement/ES/MICINN-AEI/PID2020-113463RB-C31/AEI/10.13039/501100011033

Tipo y forma: Article (Published version)

Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)