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Structure: Internal structure identifier : 161327
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Engineering empowered by physics-based and data-driven hybrid models: A methodological overview

Victor Champaney , Francisco Chinesta , Elias Cueto
International Journal of Material Forming, 2022, 15 (3), ⟨10.1007/s12289-022-01678-4⟩
Journal articles hal-03709137v1
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Real‐time interaction of virtual and physical objects in mixed reality applications

Alberto Badías , David González , Icíar Alfaro , Francisco Chinesta , Elías Cueto
International Journal for Numerical Methods in Engineering, 2020, 121 (17), pp.3849-3868. ⟨10.1002/nme.6385⟩
Journal articles hal-02954594v1

Natural Element Method for the Simulation of Structures and Processes

Francisco Chinesta , Serge Cescotto , Elías Cueto , Philippe Lorong
Wiley, pp.241, 2011, 978-1-84821-220-6. ⟨10.1002/9781118616901⟩
Books hal-01002856v1
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On the effective conductivity and the apparent viscosity of a thin rough polymer interface using PGD‐based separated representations

Amine Ammar , Chady Ghnatios , Frank Delplace , Anaïs Barasinski , Jean‐louis Duval , et al.
International Journal for Numerical Methods in Engineering, 2020, 121, pp.5256-5274. ⟨10.1002/nme.6448⟩
Journal articles hal-02902716v1
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A novel sparse reduced order formulation for modeling electromagnetic forces in electric motors

Abel Sancarlos , Elias Cueto , Francisco Chinesta , Jean-Louis Duval
SN Applied Sciences, 2021, 3, pp.1-19. ⟨10.1007/s42452-021-04310-3⟩
Journal articles hal-03269735v1
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Thermodynamically consistent data-driven computational mechanics

David González , Francisco Chinesta , Elías Cueto
Continuum Mechanics and Thermodynamics, 2018, pp.1-15. ⟨10.1007/s00161-018-0677-z⟩
Journal articles hal-01901772v1
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Crossing Scales: Data-Driven Determination of the Micro-scale Behavior of Polymers From Non-homogeneous Tests at the Continuum-Scale

Víctor J. Amores , Francisco J. Montáns , Elías Cueto , Francisco Chinesta
Frontiers in Materials, 2022, 9, pp.879614. ⟨10.3389/fmats.2022.879614⟩
Journal articles hal-03712605v1
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Learning data-driven reduced elastic and inelastic models of spot-welded patches

Agathe Reille , Victor Champaney , Fatima Daim , Yves Tourbier , Nicolas Hascoet , et al.
Mechanics & Industry, 2021, 22, pp.32. ⟨10.1051/meca/2021031⟩
Journal articles hal-03214183v1
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Data-driven GENERIC modeling of poroviscoelastic materials

Chady Ghnatios , Icíar Alfaro , David González , Francisco Chinesta , Elías G. Cueto
Entropy, 2019, 21 (12), pp.1-15. ⟨10.3390/e21121165⟩
Journal articles hal-02547932v1
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Empowering Advanced Driver-Assistance Systems from Topological Data Analysis

Tarek Frahi , Francisco Chinesta , Antonio Falco , Alberto Badias , Elias Cueto , et al.
Mathematics , 2021, 9 (6), pp.634. ⟨10.3390/math9060634⟩
Journal articles hal-03200628v1
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Data-driven upscaling of orientation kinematics in suspensions of rigid fibres

Adrien Scheuer , Amine Ammar , Emmanuelle Abisset-Chavanne , Elías Cueto , Francisco Chinesta , et al.
Computer Modeling in Engineering and Sciences, 2018, 117 (3), pp.367-386. ⟨10.31614/cmes.2018.04278⟩
Journal articles hal-02162204v1
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Regularized regressions for parametric models based on separated representations

Abel Sancarlos , Victor Champaney , Elias Cueto , Francisco Chinesta
Advanced Modeling and Simulation in Engineering Sciences, 2023, 10, pp.1-26. ⟨10.1186/s40323-023-00240-4⟩
Journal articles hal-04163203v1
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Data Completion, Model Correction and Enrichment Based on Sparse Identification and Data Assimilation

Daniele Di Lorenzo , Victor Champaney , Claudia Germoso , Elias Cueto , Francisco Chinesta
Applied Sciences, 2022, 12 (15), pp.7458. ⟨10.3390/app12157458⟩
Journal articles hal-03895734v1
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Structure-preserving neural networks

Quercus Hernández , Alberto Badías , David González , Francisco Chinesta , Elías Cueto
Journal of Computational Physics, 2020, pp.1-16. ⟨10.1016/j.jcp.2020.109950⟩
Journal articles hal-03019811v1
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An augmented reality platform for interactive aerodynamic design and analysis

Alberto Badías , Sarah Curtit , David González , Icíar Alfaro , Francisco Chinesta , et al.
International Journal for Numerical Methods in Engineering, 2019, 120 (1), pp.125-138. ⟨10.1002/nme.6127⟩
Journal articles hal-02457443v1
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MORPH-DSLAM: Model Order Reduction for Physics-Based Deformable SLAM

Alberto Badias , Iciar Alfaro , David Gonzalez , Francisco Chinesta , Elias Cueto
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44 (11), pp.7764-7777. ⟨10.1109/tpami.2021.3118802⟩
Journal articles hal-04069431v1
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Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems

Quercus Hernández , Alberto Badías , Francisco Chinesta , Elías Cueto
Computational Mechanics, 2023, 72, pp.553-561. ⟨10.1007/s00466-023-02296-w⟩
Journal articles hal-04163352v1
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Learning non-Markovian physics from data

David González , Francisco Chinesta , Elías Cueto
Journal of Computational Physics, 2020, pp.1-14. ⟨10.1016/j.jcp.2020.109982⟩
Journal articles hal-03019897v1
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Digital twins that learn and correct themselves

Beatriz Moya , Alberto Badías , Icíar Alfaro , Francisco Chinesta , Elías Cueto
International Journal for Numerical Methods in Engineering, 2022, 123 (13), pp.3034-3044. ⟨10.1002/nme.6535⟩
Journal articles hal-03709235v1
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Monitoring Weeder Robots and Anticipating Their Functioning by Using Advanced Topological Data Analysis

Tarek Frahi , Abel Sancarlos , Mathieu Galle , Xavier Beaulieu , Anne Chambard , et al.
Frontiers in Artificial Intelligence, 2021, 4, pp.761123. ⟨10.3389/frai.2021.761123⟩
Journal articles hal-04094397v1
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Effects of non idealities in switching frequency modulation techniques: Application to coupled interleaved multicellular parallel converters

Juan Mon , David Gonzalez , Lluis Ferrer-Arnau , Denis Labrousse , Francois Costa
15th European Conference on Power Electronics and Applications (EPE), 2013, Lille, France
Conference papers hal-01735855v1
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From linear to nonlinear PGD-based parametric structural dynamics

Giacomo Quaranta , Clara Argerich Martin , Rubén Ibáñez , Jean Louis Duval , Elías Cueto , et al.
Comptes Rendus Mécanique, 2019, 347 (5), pp.445-454. ⟨10.1016/j.crme.2019.01.005⟩
Journal articles hal-02165050v2
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Empowering Materials Processing and Performance from Data and AI

Francisco Chinesta , Elias Cueto , Benjamin Klusemann
Materials, 2021, 14 (16), pp.4409. ⟨10.3390/ma14164409⟩
Journal articles hal-03338858v1
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Spurious-free interpolations for non-intrusive PGD-based parametric solutions: Application to composites forming processes

Chady Ghnatios , Elias Cueto , Antonio Falco , Jean-Louis Duval , Francisco Chinesta
International Journal of Material Forming, 2020, 14 (1), pp.83-95. ⟨10.1007/s12289-020-01561-0⟩
Journal articles hal-03273813v1
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Deep learning of thermodynamics-aware reduced-order models from data

Quercus Hernandez , Alberto Badias , David Gonzalez , Francisco Chinesta , Elias Cueto
Computer Methods in Applied Mechanics and Engineering, 2021, 379, pp.113763. ⟨10.1016/j.cma.2021.113763⟩
Journal articles hal-03200622v1
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A thermodynamics-informed active learning approach to perception and reasoning about fluids

Beatriz Moya , Alberto Badías , David González , Francisco Chinesta , Elías Cueto
Computational Mechanics, 2023, ⟨10.1007/s00466-023-02279-x⟩
Journal articles hal-04086391v1
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A separated representation involving multiple time scales within the Proper Generalized Decomposition framework

Angelo Pasquale , Amine Ammar , Antonio Falcó , Simona Perotto , Elías Cueto , et al.
Advanced Modeling and Simulation in Engineering Sciences, 2021, 8 (26), pp.1-22. ⟨10.1186/s40323-021-00211-7⟩
Journal articles hal-04096707v1
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Thermodynamics-informed neural networks for physically realistic mixed reality

Quercus Hernández , Alberto Badías , Francisco Chinesta , Elías Cueto
Computer Methods in Applied Mechanics and Engineering, 2023, 407, pp.115912. ⟨10.1016/j.cma.2023.115912⟩
Journal articles hal-04073075v1