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 :
Hugo De Oliveira
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Seminar
Location
LISN Site Belvédère
Speaker :
Akram Elbouanani
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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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Article dans une revue
Jay Amrit, Ye. Nemchenko, K. Nemchenko, I. Kudryavtsev, S. Rogova, et al.. Unusual heat transfer dependence on boundary scattering in very long narrow conductors. Low Temperature Physics, 2024, 50 (5), pp.364-367. ⟨10.1063/10.0025618⟩. ⟨hal-05240571⟩
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Article dans une revue
Jay Amrit, T. Medintseva, K. Niemchenko, Ye. Niemchenko, S. Rogova, et al.. Influence of specularity factor on heat transport in nanoribbons of different sizes. Low Temperature Physics, 2024, 50 (10), pp.891-897. ⟨10.1063/10.0028629⟩. ⟨hal-05240556⟩
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Article dans une revue
Jay Amrit, K. Niemchenko, Ye. Niemchenko, S. Rogova, T. Vikhtynska. Heat transfer in conductors of cylindrical cross-section with diffusive boundary scattering. Low Temperature Physics, 2025, 51 (1), pp.37-42. ⟨10.1063/10.0034642⟩. ⟨hal-05240736⟩
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Article dans une revue
Jay Amrit, N. Herashchenko, K. Nemchenko, S. Rogova, T. Vikhtinskaya. Two-mode dissipation of oscillating tuning fork in 3He–4He superfluid mixtures. Low Temperature Physics, 2025, 51 (1), pp.5-9. ⟨10.1063/10.0034553⟩. ⟨hal-05240727⟩
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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⟩