The activities of the department are grouped around Fluid Mechanics, Mass and Heat Transfer and Energetics. We conduct research of a generally fundamental nature, with applications in the energy, transport, health and environment sectors.
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.
Emmanuella Martinod. Apports d'une approche pluridisciplinaire pour la description de langues des signes micro-communautaires. Multidimensionnalité, transdisciplinarité : à la croisée des approches en Sciences du langage, École Doctorale 268 « Langage et langues »; Université Sorbonne Nouvelle, Jun 2020, PARIS, France. ⟨hal-04006826⟩
Atilla Kaan Alkan, Cyril Grouin, Fabian Schüssler, Pierre Zweigenbaum. TDAC, the First Time-Domain Astrophysics Corpus: Analysis and First Experiments on Named Entity Recognition. Workshop on Information Extraction from Scientific Publications, Nov 2022, Taipei (Online), Taiwan. ⟨hal-04046837⟩
Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, Pierre Zweigenbaum. Specializing Static and Contextual Embeddings in the Medical Domain Using Knowledge Graphs: Let's Keep It Simple. International Workshop on Health Text Mining and Information Analysis (LOUHI), Dec 2022, Abu Dhabi (online), United Arab Emirates. ⟨hal-04046746⟩
Clément Gain, Bénédicte Rhoné, Philippe Cubry, Israfel Salazar, Florence Forbes, et al.. A quantitative theory for genomic offset statistics. 2023. ⟨hal-04049450⟩
Fabrice Popineau. Approche Logique de la Personnalisation dans les Environnements Informatiques pour l'Apprentissage Humain. Environnements Informatiques pour l'Apprentissage Humain. Université Paris-Saclay, 2023. Français. ⟨NNT : 2023UPASG001⟩. ⟨tel-04047319⟩
Mohammad Alaul Islam. Visualizations for Smartwatches and Fitness Trackers. Computer science. Université Paris-Saclay, 2023. English. ⟨NNT : 2023UPASG018⟩. ⟨tel-04047471⟩
Michele De Bonis, Huyen Nguyen, Patrick Bourdot. A Literature Review of User Studies in Extended Reality Applications for Archaeology. 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Oct 2022, Singapore, Singapore. pp.92-101, ⟨10.1109/ISMAR55827.2022.00023⟩. ⟨hal-04021383⟩
Jules Françoise, Baptiste Caramiaux. Marcelle : un toolkit pour la conception d’interactions humain-apprentissage automatique. IHM 2023 – 34e Conférence Internationale Francophone sur l'Interaction Humain-Machine, AFIHM; Université de Technologie de Troyes, Apr 2023, Troyes, France. ⟨hal-04043369⟩
Camille Gobert. Projecting Computer Languages for a Semantic Interaction. IHM'23 – 34e Conférence Internationale Francophone sur l'Interaction Humain-Machine, AFIHM; Université de Technologie de Troyes, Apr 2023, Troyes, France. ⟨hal-04042356⟩