Computing and Fluids – CFL

    https://www.cemef.minesparis.psl.eu/wp-content/uploads/2020/01/0-1000x400.jpg

    Permanent Members

    Elie Hachem, leader
    Jérémie Bec (CNRS)
    Romain Castellani
    Thierry Coupez
    Patrice Laure (CNRS)
    Aurélien Larcher
    Philippe Meliga (CNRS)
    Youssef Mesri
    Edith Peuvrel-Disdier (CNRS)
    Franck Pigeonneau
    Rudy Valette

    About

    Welcome to the Computing and Fluids research group at CEMEF, Mines Paris.
    We are interested in developing new methods and techniques to address a number of problems in engineering, physics and life sciences. We focus on massively parallel numerical methods to efficiently model processes and physical phenomena at different industrial scales. We make use of experimental techniques to complement and validate our models.

    Much of our research involves Computational Mathematics and Mechanics, Mesh adaptation with error estimators, High Performance Computing, Experimental and Computational Fluid Dynamics (CFD) using Stabilized FEM and Variational MultiScale methods for:

    •  Complex and non-Newtonian fluids
    • Free surface and Multiphase Flows
    • Machine learning for fluid mechanics
    • Phase change and Conjugate heat transfer
    • Turbulence and fluid-structure interaction
    • Aerodynamics, wing engineering & performance

    Feel free to visit us at CFL - CEMEF or to contact us if you have questions.

    Illustrations

    Turbulent flows past an airplace
    Turbulent flows past an airplace
    Thales Alenia
    Thales Alenia
    simulation
    simulation
    The collapse of a water column with dynamic anisotropic meshing
    The collapse of a water column with dynamic anisotropic meshing
    several simulations
    several simulations
    example
    example
    the different steps
    the different steps

    "CEMEF combines strong scientific expertise in experimentation, modelling and numerics on industrial projects. It is this multidisciplinarity that motivated me to join the centre."

    Aurélien LARCHER, Professor-Researcher

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    On going PhD projects

    • Ricardo ELKHOURI : Biopolymer drag reduction in turbulent flow. MathNum specialty, Class of 2023
    • Paul GARNIER : Personalized Aneurysm Treatment using Large Physics Informed Models. MathNum specialty, Class of 2023
    • Nicolas HERTEL : Modelling of viscoelastic dewetting flows. MNM specialty, Class of 2023
    • Vincent LANNELONGUE : Computational mechanics and deep learning for intracranial aneurysm rupture risk stratification. MathNum specialty, Class of 2023
    • Xuan Minh Vuong NGUYEN : Coupling of Deep Reinforcement Learning (DRL) methods with convolutional neural networks on graphs, for the simulation and optimization of flows. MathNum specialty, Class of 2023
    • Ugo PELISSIER : Coupling artificial intelligence and digital mechanics for the treatment of intracranial aneurysms. MathNum specialty, Class of 2023
    • Eliane YOUNES : Artificial Intelligence and digital twins in metallurgy – Front-tracking modeling of evolving interface networks. MathNum specialty, Class of 2023 + MSR team
    • Tony ZAAYTER : Deep reinforcement learning for innovative design and development of digital twins for flask’s molds. MathNum specialty, Class of 2023
    • Léa CAILLY-BRANDSTÄTER : Instabilities and texturing under flow of thin layers of non-Newtonian fluids. MNM specialty, Class of 2022
    • Clément GAULTIER : Anisotropic Mesh Adaptation for Multiphase Flow Dynamicswith wetting and capillarity effectsin coating applications. MathNum specialty, Class of 2022
    • Théodore MICHEL : Digital Twin of a photovoltaic power plant. MathNum specialty, Class of 2022
    • Abdelilah RBAH : Fluid-Structure interaction of intracranial aneurysm: modeling, simulation and risk evaluation. MathNum specialty, Class of 2022
    • Maxime RENAULT : Numerical simulation of the aorta by finite element method and application of optimization methods for the improvement of a ventricular assist device. MathNum specialty, Class of 2022
    • Wael BADER : Resolution strategies for computational mechanics using randomized linear algebra with controlled precision. MathNum specialty, Class of 2021
    • Jennifer EL ZAHABI : Advanced numerical modeling and simulation of the Lost Foam process. MathNum specialty, Class of 2021
    • Aurèle GOETZ : Development of a solid solver for complex behaviors. MathNum specialty, Class of 2021 + CSM team
    • Kindness ISUKWEM : Impact of non-Newtonian drops on liquids. MNM specialty, Class of 2021
    • Pablo JEKEN RICO : Remeshing of complex geometries by GPU. Class of 2021
    • Alan TABORÉ : Modeling of residual stresses in an ophthalmic lens. MNM specialty, Class of 2021 + MPI team
    • Sujie YU : Experimental studies of the formation of gels and aerogels (dry gels) based on natural polymers, cellulose and these industrial derivatives (methyl cellulose, hydroxypropyl cellulose). MNM specialty, Class of 2021 + CFL team
    • Thibaut DEVOS : Numerical development in C++ and finite elements of a two-phase aerothermal solver for additive manufacturing applications such as cold spraying for coating materials. MathNum specialty, Class of 2020
    • Juan ITRIAGO : Cellularization of an elastomer in injection: Modeling of the process/physical process coupling to predict the cell microstructure. MNM specialty, Class of 2020