163253 20251024172258.0 doi 10.1186/s40323-025-00311-8 sideral 145765 ART-2025-145765 eng Bermejo, Carlos Universidad de Zaragoza Meshgraphnets informed locally by thermodynamics for the simulation of flows around arbitrarily shaped objects 2025 We present a thermodynamics-informed graph neural network framework for learning the time evolution of complex physical systems, incorporating thermodynamic structure via a nodal port-metriplectic formulation. Built upon the MeshGraphNet architecture, our method replaces the standard decoder with multiple specialized decoders that predict local energy and entropy gradients, along with Poisson and dissipative operators. These components are assembled at each graph node according to the GENERIC formalism, enforcing the first and second laws of thermodynamics. The framework is evaluated on two examples involving incompressible fluid flow past obstacles: one with varying cylindrical obstacles and another with obstacles of different types, not seen during training. The proposed model shows accurate long-term predictions, robust generalization to unseen geometries, and substantial speedups compared to traditional numerical solvers. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/MICINN/PID2023-147373OB-I00 info:eu-repo/grantAgreement/ES/MTFP/TSI-100930-2023-1 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Badías, Alberto (orcid)0000-0001-7639-6767 González, David Universidad de Zaragoza (orcid)0000-0003-3003-5856 Cueto, Elías Universidad de Zaragoza (orcid)0000-0003-1017-4381 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 12, 1 (2025), [18 pp.] Adv. model. simul. eng. sci. Advanced modeling and simulation in engineering sciences 2213-7467 3037454 http://zaguan.unizar.es/record/163253/files/texto_completo.pdf Versión publicada 2244071 http://zaguan.unizar.es/record/163253/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:163253 articulos driver 2025-10-24-16:55:49 ARTICLE