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Didier Lucor
CNRS research director and Deputy Director of the LISN lab on Paris-Saclay university campus in Orsay
64%
Libre accès
11
Documents
Affiliations actuelles
- 1061259
- 1055806
Identifiants chercheurs
didier-lucor-
0000-0003-4334-4586
- Google Scholar : https://scholar.google.com/citations?user=qCVFS6AAAAAJ&hl=en
- IdRef : 150876017
Présentation
Currently a research director at the French National Research Agency (CNRS) and deputy director of the LISN lab on Paris-Saclay campus in Orsay, France. I'm a member of the DATAFLOT (DAta science, TrAnsition, FLuid instabiLity, contrOl & Turbulence) research group of the Mechanical Engineering department. I received my PhD (2004) in Applied Math. from Brown University; was a postdoctoral fellow (2004-2005) in the dpt of Ocean Eng at MIT. My research interests relate to stochastic modeling and computational mechanics, with emphasis on: physics-informed statistical learning, reduced-order modeling, uncertainty quantification, data assimilation, sensitivity analysis and robust optimization.
Applications in computational mechanics range from turbulence modeling, heat transfer, flow-structure interaction problems to biomechanics, environmental flows and fluid mechanics related to the energy sector.
Publications
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Simple computational strategies for more effective physics-informed neural networks modeling of turbulent natural convectionJournal of Computational Physics, 2022, 456, pp.111022. ⟨10.1016/j.jcp.2022.111022⟩
Article dans une revue
hal-03847907v1
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Physics-informed neural networks modeling of turbulent natural convectionPiAI Seminar Series: Physics informed AI in Plasma Science, Japan Society for the Promotion of Science - Osaka University - TAMU, Jan 2023, Webinaire, Japan
Communication dans un congrès
hal-04400143v1
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Temperature field inference using physics-informed neural networks in turbulent natural convection22nd IACM Computational Fluids Conference – CFC 2023, IACM, Apr 2023, Cannes, France
Communication dans un congrès
hal-04400813v1
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Plumes and large scale circulation in turbulent thermal convection with a rough plateRBC 2023 - 9th International Conference on Rayleigh-Bénard Turbulence, Oct 2023, Xi'an, China
Communication dans un congrès
hal-04400263v1
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Panaches turbulents en convection turbulente de Rayleigh-BénardConvection naturelle : aspects fondamentaux et applications, Journées d'étude de la Société Française de Thermique, Jul 2023, Orsay, France
Communication dans un congrès
hal-04401159v1
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Super-résolution par apprentissage automatique guidé par la physique : évaluation pour la convection turbulente25ème Congrès Français de Mécanique (CFM 2022), AFM, Aug 2022, Nantes, France. pp.159-168
Communication dans un congrès
hal-04400566v1
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PHYSICS/DNS-INFORMED DNN SURROGATES OF TURBULENT THERMAL CONVECTION14th World Congress on Computational Mechanics (WCCM) ECCOMAS Congress 2020, ECCOMAS, Jul 2020, Paris, France
Communication dans un congrès
hal-04400889v1
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Réseaux de neurones informés par la physique : application à la convection turbulenteJournée de dynamique des fluides du plateau de Saclay, Feb 2020, Orsay, France
Communication dans un congrès
hal-04401239v1
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PDE-CONSTRAINED NEURAL NETWORK FOR TURBULENT RAYLEIGH-B ÉNARD CONVECTIONEuropean Numerical Mathematics and Advanced Applications Conference (ENUMATH2019), Sep 2019, Egmond aan Zee, Netherlands
Communication dans un congrès
hal-04400942v1
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Investigation of PDE-constrained deep neural networks for efficient flow field assimilationWorkshop on Frontiers of Uncertainty Quantification in Fluid Dynamics, Sep 2019, Pise (Italie), Italy
Communication dans un congrès
hal-04400958v1
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Physics-aware deep neural networks for surrogate modeling of turbulent natural convection2021
Pré-publication, Document de travail
hal-03159996v1
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