Publications des membres du GdR

En affectant le mot clé « I-GAIA » à leurs publications dans l’archive ouverte Hal, les participants du GDR voient leurs publications associées à la collection Hal du GdR (https://hal.science/GDRIGAIA).

Celle-ci comporte 23 publications à l’heure actuelle. Les dernières sont listées ci-dessous par catégories.



23 documents

Articles dans une revue

  • Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework.. Computer Methods in Applied Mechanics and Engineering, 2024, 425, pp.116967. ⟨10.1016/j.cma.2024.116967⟩. ⟨hal-04368755⟩
  • Pramudita Satria Palar, Yohanes Bimo Dwianto, Lavi Rizki Zuhal, Joseph Morlier, Koji Shimoyama, et al.. Multi-objective design space exploration using explainable surrogate models. Structural and Multidisciplinary Optimization, 2024, 67 (38), ⟨10.1007/s00158-024-03769-z⟩. ⟨hal-04512428⟩
  • Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. NN-mCRE: a modified Constitutive Relation Error framework for unsupervised learning of nonlinear state laws with physics-augmented Neural Networks. International Journal for Numerical Methods in Engineering, 2024, ⟨10.1002/nme.7439⟩. ⟨hal-04102108v2⟩
  • Paul Saves, Rémi Lafage, Nathalie Bartoli, Youssef Diouane, Jasper Bussemaker, et al.. SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes. Advances in Engineering Software, 2024, 188 (103571), pp.103571. ⟨10.1016/j.advengsoft.2023.103571⟩. ⟨hal-04331916⟩
  • Héloïse Dandin, Adrien Leygue, Laurent Stainier. Graph-based representation of history-dependent material response in the Data-Driven Computational Mechanics framework. Computer Methods in Applied Mechanics and Engineering, 2023, 419, pp.116694. ⟨10.1016/j.cma.2023.116694⟩. ⟨hal-04259707v2⟩
  • Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier. Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm. Aerospace Science and Technology, 2023, 142 (Part B), ⟨10.1016/j.ast.2023.108673⟩. ⟨hal-04254361⟩
  • Benoit Hilloulin, Abdelhamid Hafidi, Sonia Boudache, Ahmed Loukili. Interpretable ensemble machine learning for the prediction of the expansion of cementitious materials under external sulfate attack. Journal of Building Engineering, 2023, pp.107951. ⟨10.1016/j.jobe.2023.107951⟩. ⟨hal-04255480⟩
  • Paul Saves, Y. Diouane, N. Bartoli, T. Lefebvre, J. Morlier. A mixed-categorical correlation kernel for Gaussian process. Neurocomputing, In press, ⟨10.1016/j.neucom.2023.126472⟩. ⟨hal-04130877v2⟩
  • Afsal Pulikkathodi, Elisabeth Longatte-Lacazedieu, Ludovic Chamoin, Juan-Pedro Berro Ramirez, Laurent Rota, et al.. A neural network-based data-driven local modeling of spotwelded plates under impact. Mechanics & Industry, 2023, 24, pp.34. ⟨10.1051/meca/2023029⟩. ⟨hal-04190457⟩
  • Benoit Hilloulin, van Quan Tran. Interpretable machine learning model for autogenous shrinkage prediction of low-carbon cementitious materials. Construction and Building Materials, 2023, 396, pp.132343. ⟨10.1016/j.conbuildmat.2023.132343⟩. ⟨hal-04153200⟩
  • Benoit Hilloulin, Mathieu Lagrange, Marius Duvillard, Gauthier Garioud. ε-greedy automated indentation of cementitious materials for phase mechanical properties determination. Cement and Concrete Composites, 2022, 129, ⟨10.1016/j.cemconcomp.2022.104465⟩. ⟨hal-03596856v2⟩
  • Benoit Hilloulin, van Quan Tran. Using machine learning techniques for predicting autogenous shrinkage of concrete incorporating superabsorbent polymers and supplementary cementitious materials. Journal of Building Engineering, In press, ⟨10.1016/j.jobe.2022.104086⟩. ⟨hal-03541648⟩
  • Cindy Trinh, Dimitrios Meimaroglou, Sandrine Hoppe. Machine Learning in Chemical Product Engineering: The State of the Art and a Guide for Newcomers. Processes, 2021, 9, ⟨10.3390/pr9081456⟩. ⟨hal-03367703⟩
  • Benoit Hilloulin, Maxime Robira, Ahmed Loukili. Coupling statistical indentation and microscopy to evaluate micromechanical properties of materials: Application to viscoelastic behavior of irradiated mortars. Cement and Concrete Composites, 2018, 94, pp.153 – 165. ⟨10.1016/j.cemconcomp.2018.09.008⟩. ⟨hal-01938271⟩

Communications dans un congrès

  • Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage, Paul Saves, Youssef Diouane, et al.. Multi-objective bayesian optimization with mixed-categorical design variables for expensive-to-evaluate aeronautical applications. AEROBEST 2023, ECCOMAS, Jul 2023, Lisbonne, Portugal. pp.436. ⟨hal-04170287⟩
  • Abdelhamid Hafidi, Benoit Hilloulin, Sonia Boudache, Umunnakwe Rejoice, Ahmed Loukili. Comparison of Machine Learning Algorithms for the Prediction of the External Sulphate Attack Resistance of Blended Cements. International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures. SynerCrete 2023., Jun 2023, Milos Island, Greece. pp.725-735, ⟨10.1007/978-3-031-33187-9_67⟩. ⟨hal-04131990⟩
  • Ludovic Chamoin, Antoine Benady, Sahar Farahbakhsh, Emmanuel Baranger, Martin Poncelet. Data-based Model Updating, Selection, and Enrichment using the Modified Constitutive Relation Error Concept. 15th World Congress on Computational Mechanics, Jul 2022, Yokohama, Japan. ⟨hal-04000251⟩
  • Robin Grapin, Youssef Diouane, Joseph Morlier, Nathalie Bartoli, Thierry Lefebvre, et al.. Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design. AIAA AVIATION 2022, Jun 2022, Chicago, United States. ⟨10.2514/6.2022-4053⟩. ⟨hal-03753674⟩
  • Paul Saves, Youssef Diouane, Nathalie Bartoli, Thierry Lefebvre, Joseph Morlier. A general square exponential kernel to handle mixed-categorical variables for Gaussian process. AIAA AVIATION 2022 Forum, Jun 2022, Chicago (virtual), France. ⟨10.2514/6.2022-3870⟩. ⟨hal-03700850⟩
  • Raul Carreira Rufato, Youssef Diouane, Joël Henry, Richard Ahlfeld, Joseph Morlier. A mixed-categorical data-driven approach for prediction and optimization of hybrid discontinuous composites performance. AIAA AVIATION 2022 Forum, Jun 2022, Chicago, United States. pp.0, ⟨10.2514/6.2022-4037⟩. ⟨hal-03888070⟩
  • Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier. Multi-fidelity constrained Bayesian optimization, application to drone design. Conference on Artificial Intelligence for Defense CAID, Direction Générale de l’Armement (DGA), Nov 2021, Rennes, France. ⟨hal-03891316v4⟩

Pré-publications, Documents de travail

  • Renaud Ferrier, Mohamed Larbi Kadri, Sylvain Drapier, Pierre Gosselet. Apprentissage automatique d’EDPs contraintes par la physique pour l’identification des hétérogénéités dans les structures mécaniques élancées. 2023. ⟨hal-04230541⟩

Rapports

  • Edgar Zembra, Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Use of physics-augmented neural networks for unsupervised learning of material constitutive relations – Comparison of the NN-Euclid and NN-mCRE methods. ENS Paris-Saclay; Centrale Supélec. 2023. ⟨hal-04255767⟩