Computational Structural Mechanics Association

Collections HAL

Le CSMA gère deux collections HAL qui regroupent:

Publications AMSES


280 documents

  • Yinghan Wu, Kaixuan Shao, Francesco Piccialli, Gang Mei. Numerical modeling of the propagation process of landslide surge using physics-informed deep learning. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-15. ⟨10.1186/s40323-022-00228-6⟩. ⟨hal-04456076⟩
  • Terrin Stachiw, Alexander Crain, Joseph Ricciardi. A physics-based neural network for flight dynamics modelling and simulation. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-20. ⟨10.1186/s40323-022-00227-7⟩. ⟨hal-04456077⟩
  • Valerie A. Martin, Reuben H. Kraft, Thomas H. Hannah, Stephen Ellis. An energy-based study of the embedded element method for explicit dynamics. Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-18. ⟨10.1186/s40323-022-00223-x⟩. ⟨hal-04513972⟩
  • E. Rajasekhar Nicodemus. A methodology to assess and improve the physics consistency of an artificial neural network regression model for engineering applications. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-29. ⟨10.1186/s40323-022-00224-w⟩. ⟨hal-04456078⟩
  • Sebastián Cedillo, Ana Gabriela Núñez, Esteban Sánchez-Cordero, Luis Timbe, Esteban Samaniego, et al.. Physics-Informed Neural Network water surface predictability for 1D steady-state open channel cases with different flow types and complex bed profile shapes. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-23. ⟨10.1186/s40323-022-00226-8⟩. ⟨hal-04458286⟩
  • Nora Hagmeyer, Matthias Mayr, Ivo Steinbrecher, Alexander Popp. One-way coupled fluid–beam interaction: capturing the effect of embedded slender bodies on global fluid flow and vice versa. Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-30. ⟨10.1186/s40323-022-00222-y⟩. ⟨hal-04513974⟩
  • Jan Oldenburg, Finja Borowski, Alper Öner, Klaus Peter Schmitz, Michael Stiehm. Geometry aware physics informed neural network surrogate for solving Navier–Stokes equation (GAPINN). Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-15. ⟨10.1186/s40323-022-00221-z⟩. ⟨hal-04513973⟩
  • Harald Willmann, Wolfgang A. Wall. Inverse analysis of material parameters in coupled multi-physics biofilm models. Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-32. ⟨10.1186/s40323-022-00220-0⟩. ⟨hal-04513976⟩
  • Fabio Giampaolo, Mariapia de Rosa, Pian Qi, Stefano Izzo, Salvatore Cuomo. Physics-informed neural networks approach for 1D and 2D Gray-Scott systems. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning Francesco Piccialli, 9 (1), pp.1-17. ⟨10.1186/s40323-022-00219-7⟩. ⟨hal-04456081⟩
  • Hanane Khatouri, Tariq Benamara, Piotr Breitkopf, Jean Demange. Metamodeling techniques for CPU-intensive simulation-based design optimization: a survey. Advanced Modeling and Simulation in Engineering Sciences, 2022, Efficient strategies for surrogate-based optimization including multifidelity and reduced-order models, 9 (1), pp.1-31. ⟨10.1186/s40323-022-00214-y⟩. ⟨hal-04458288⟩

Documents récupérés de l'archive ouverte HAL logo

Publications CSMA (Giens)


2438 documents

  • Morgane Suhas, Emmanuelle Abisset-Chavanne, Pierre-André Rey. Renforcement de la robustesse d'un modèle hybride de pronostic de défaillances d'un moteur électrique par apprentissage progressif. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04611032⟩
  • Cédric Bellis, Renaud Ferrier. Adaptive computations on non-uniform grids by optimal transport in FFT-based homogenization. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04610885⟩
  • Thomas Leyssens, Jonathan Lambrechts, Jean-François Remacle. Un Algorithme d'Adaptation de Maillage pour la Simulation d'Ecoulements à Surface Libre dans la Méthode des Eléments Finis-Particules (PFEM). 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04611053⟩
  • Arnaud Duval, Thomas Elguedj. YETI – Nouvelles fonctionnalités d'optimisation de forme en IGA. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04611069⟩
  • Vincent Longchamp, Jérémie Girardot, Damien André, Frédéric Malaise, Ivan Iordanoff. Analyse numérique de l'endommagement dynamique à l'échelle de la microstructure par simulation discrète. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04610894⟩
  • Abbas Kabalan, Fabien Casenave, Felipe Bordeu, Virginie Ehrlacher, Alexandre Ern. Morphing techniques for model order reduction with non parametric geometrical variabilities. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04611002⟩
  • Martin Genet, Mahdi Manoochehr Tayebi, Aline Bel Brunon. Un modèle micro-poro-mécanique du parenchyme pulmonaire. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04611056⟩
  • Etienne Pruliere, Yves Chemisky. 3MAH : un ensemble de librairies pour analyser le comportement complexe de matériaux hétérogènes. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04610878⟩
  • Michel Henry, Stéphane Dorbolo, Frédéric Dubois, Jonathan Lambrechts, Vincent Legat. La modélisation du tranfert de chaleur dans les écoulements granulaires immergés par une approche multi-échelle. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04822992⟩
  • Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Apprentissage non-supervisé de lois de comportement non- linéaires avec réseau de neurones thermodynamiquement consistent par minimisation de l'erreur en relation de comportement modifiée. 16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2024, Hyères, France. ⟨hal-04822948⟩

Documents récupérés de l'archive ouverte HAL logo