Approach and perspective
The approach of the Mechanics-Energetics department is at the interface between computer science, physics and applied mathematics.
We wish to maintain a balance between interdependent activities:
- understanding the fundamental phenomena of turbulent fluid mechanics,
- tackling complex multiphysics problems coupled at large scales,
- leveraging our physical knowledge while considering data as an inherent part of modeling, experiments and simulations.
In this context, we are very open to recent developments in machine learning, which offer a powerful information processing framework that can augment our current lines of research with broad-spectrum applications in the energy, transportation, health, and environmental sectors.
Organization
The Mechanics-Energetics Department offers original and multidisciplinary research thanks to the expertise of some twenty permanent staff, researchers, teacher-researchers and engineers, organized into two complementary teams: DATAFLOT (DAta science, TrAnsition, FLuid instabiLity, contrOl & Turbulence) relying on data-augmented modeling and artificial intelligence, and studying fluid dynamics, instabilities and turbulence, and COMET (COuplages MultiphysiquEs et Transferts) focusing on the understanding of complex coupled fluid phenomena, involved in energy conversion and storage, heat transfers as well as energy efficiency optimization.
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Data Science, Thesis
Speaker :
Francesca Bugiotti
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Article dans une revue
Miguel Quetzeri-Santiago, C. Ricardo Constante-Amores, Thomas Sykes, Seungwon Shin, Jalel Chergui, et al.. Droplet impact and splashing on surfactant-laden shallow pools. International Journal of Multiphase Flow, 2025, 193, pp.105387. ⟨10.1016/j.ijmultiphaseflow.2025.105387⟩. ⟨hal-05216255⟩
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Thèse
Jiayi Cai. Turbulence modeling using machine learning driven by direct numerical simulations. Fluid mechanics [physics.class-ph]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPAST171⟩. ⟨tel-05215057⟩
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Article dans une revue
Edgar Jaber, Vincent Blot, Nicolas Brunel, Vincent Chabridon, Emmauel Remy, et al.. Conformal Approach to Gaussian Process Surrogate Evaluation with Coverage Guarantees. Journal of Machine Learning for Modeling and Computing, 2025, 6 (3), pp.37-68. ⟨10.1615/JMachLearnModelComput.2025054687⟩. ⟨hal-05161190⟩
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Communication dans un congrès
Sami Tliba, Luca Greco, Mohamed Yazid Rizi, Luc Pastur, François Lusseyran, et al.. Identification of a plasma actuated open-cavity under flow control. 2025 Joint IFAC Conference SSSC, TDS, COSY, CentraleSupélec, Jun 2025, Gif-sur-Yvette, France. ⟨hal-05148991⟩
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Pré-publication, Document de travail
Edgar Jaber, Emmanuel Remy, Vincent Chabridon, Mathilde Mougeot, Didier Lucor. Fusion of heterogeneous data for robust degradation prognostics. 2025. ⟨hal-05091317⟩
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Article dans une revue
P. Pico, L. Kahouadji, S. Shin, J. Chergui, Damir Juric, et al.. Surfactant-laden bubble bursting: dynamics of capillary waves and Worthington jet at large Bond number. Physical Review Fluids, 2024, 9 (8), pp.083606. ⟨10.1103/PhysRevFluids.9.083606⟩. ⟨hal-05083568⟩
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Article dans une revue
Abdullah Abdal, Lyes Kahouadji, Seungwon Shin, Jalel Chergui, Damir Juric, et al.. Pairwise interaction of in-line spheroids settling in a linearly-stratified fluid. Acta Mechanica, 2024, ⟨10.1007/s00707-024-04125-4⟩. ⟨hal-05083569⟩
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Thèse
Remy Hosseinkhan-Boucher. On Learning-Based Control of Dynamical Systems. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2025. English. ⟨NNT : 2025UPASG029⟩. ⟨tel-05061303⟩
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Article dans une revue
Debashis Panda, Lyes Kahouadji, Laurette Tuckerman, Seungwon Shin, Jalel Chergui, et al.. Marangoni-driven patterns, ridges, and hills in surfactant-covered parametric surface waves. Journal of Fluid Mechanics, 2025, 1008, pp.R4. ⟨10.1017/jfm.2025.245⟩. ⟨hal-05029962⟩
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Article dans une revue
Ying Wang, Anne Sergent, Didier Saury, Denis Lemonnier, Patrice Joubert. Gas radiation effect on a turbulent thermal plume in a confined cavity using direct numerical simulation. International Journal of Thermal Sciences, 2025, 213, pp.109820. ⟨10.1016/j.ijthermalsci.2025.109820⟩. ⟨hal-04997739⟩