Research reports/preprints

2026/04
A Graph Neural Network approach to zero-shot Digital Twins.
A. Tierz, I. Alfaro, D. González, E. Cueto
Submitted, 2026.

2026/03
Physics-informed, Generative Adversarial Design of Funicular Shells.
Rúben Lourenço, Icíar Alfaro, Beatriz Moya, Elías Cueto.
Submitted, 2026.

2026/02
Variational Graph Neural Networks for Uncertainty Quantification in Inverse Problems
David Gonzalez, Alba Muixi, Beatriz Moya, Elias Cueto
Submitted, 2026.

2026/01
MeshGraphNet-Transformer: Scalable Mesh-based Learned Simulation for Solid Mechanics
Mikel M. Iparraguirre, Iciar Alfaro, David Gonzalez, Elias Cueto
Submitted, 2026.

2025/06
Variational Rank Reduction Autoencoders for Generative thermal design.
Alicia Tierz, Jad Mounayer, Beatriz Moya, Francisco Chinesta.
Submitted, 2025.

2025/05
MeshGraphNets informed locally by thermodynamics for the simulation of flows around arbitrarily shaped objects.
C. Bermejo, A. Badias, D. Gonzalez, E. Cueto.
Advanced Modeling and Simulation in Engineering Sciences, Volume 12, article number 27, (2025).

2025/04
Can Transformes overcome the lack of data in the simulation of history-dependent flows?
Pau Urdeitx, Icíar Alfaro, David González, Francisco Chinesta, Elías Cueto.
Submitted, 2025.

2025/03
A Gentle Introduction to Data, Learning, and Model Order Reduction.
Francisco Chinesta, Elías Cueto, Victor Champaney, Chady Ghnatios, Amine Ammar, Nicolas Hascoët, David González, Icíar Alfaro, Daniele Di Lorenzo, Angelo Pasquale, Dominique Baillargeat.
Springer, 2025.

2025/02
On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition.
Lucas Tesan, Mikel M. Iparraguirre, David Gonzalez, Pedro Martins, Elias Cueto.
Computer Methods in Applied Mechanics and Engineering, Volume 449, Part A, 1 February 2026, 118476.

2025/01
Variational Rank Reduction Autoencoder. Jad Mounayer, Alicia Tierz, Jerome Tomezyk, Chady Ghnatios, Francisco Chinesta.
Submitted, 2025.

2024/09
Physics-informed and graph neural networks for enhanced inverse analysis.
Daniele Di Lorenzo, Victor Champaney, Chady Ghnatios, Elias Cueto, Francisco Chinesta. Engineering Computations 2024; https://doi.org/10.1108/EC-12-2023-0958

2024/08
Thermodynamics-informed graph neural networks for real-time simulation of digital human twins
Lucas Tesán, David González, Pedro Martins, Elías Cueto.
Computational Mechanics, Volume 76, pages 923–944, (2025) [Open Acces].

2024/07
On the feasibility of foundational models for the simulation of physical phenomena
Alicia Tierz, Mikel M. Iparraguirre, Icíar Alfaro, David González, Francisco Chinesta, Elías Cueto.
International Journal for Numerical Methods in Engineering, 2025.

2024/06
Graph neural networks informed locally by thermodynamics.
Alicia Tierz, Icíar Alfaro, David González, Francisco Chinesta, Elías Cueto.
Engineering Applications of Artificial Intelligence, 144, 2025, 110108.

2024/05
An indirect training approach for implicit constitutive modelling using recurrent neural networks and the virtual fields method.
R. Lourenço, P. Georgieva, E. Cueto, A. Andrade-Campos.
Computer Methods in Applied Mechanics and Engineering, 425, 116961, 2024.

2024/04
A comparison of Single and Double Generator Formalisms for Thermodynamics-Informed Neural Networks.
P. Urdeitx, I. Alfaro, D. Gonzalez, F. Chinesta, E. Cueto.
Comput Mech (2024).
https://doi.org/10.1007/s00466-024-02564-3

2024/03
A Neural Network Architecture for Physically-consistent Haptic Rendering.
Q. Hernandez, P. Martins, L. Tesan, I. Alfaro, D. Gonzalez, F. Chinesta, E. Cueto.
Virtual Reality, Volume 29, article number 114, (2025)

2024/02
Thermodynamics-informed super-resolution of scarce temporal dynamics data.
C. Bermejo-Barbanoj, B. Moya, A. Badías, F. Chinesta, E. Cueto.
Computer Methods in Applied Mechanics and Engineering, Volume 430, 1 October 2024, 117210.

2024/01
Structure-preserving formulations for data-driven analysis of coupled multi-physics systems.
Alba Muixí, David González, Francisco Chinesta, Elías Cueto. Computational Mechanics, Volume 75, pages 357–368, (2025).
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