Keywords
Team
CFL - Calcul Intensif et Mécanique des Fluides
Biography
Aurélien Larcher is a researcher specializing in computational fluid dynamics and advanced simulation methods for multiphysical problems. His work focuses on developing innovative strategies to optimize the computational costs of numerical simulations, particularly through the use of anisotropic mesh adaptation, iterative solution methods, and the integration of machine learning techniques. His expertise also extends to the modeling of fluid-structure interactions (FSI), with specific applications to vascular pathologies such as intracranial aneurysms, where he evaluates the impact of modeling assumptions on hemodynamic indicators. Aurélien Larcher also contributes to shape optimization and flow control by combining multiscale variational (VMS) approaches, level-set methods, and deep reinforcement learning (DRL) algorithms, opening up new possibilities for patient-specific solutions or optimized industrial designs.
Publication(s)
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2024
Adaptive stopping criterion of iterative solvers for efficient computational cost reduction: Application to Navier–Stokes with thermal coupling DOI : 10.1016/j.finel.2024.104263
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2024
Adaptive Immersed Mesh Method (AIMM) for Fluid–Structure Interaction DOI : 10.1016/j.compfluid.2024.106285
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2024
Analysis of Intracranial Aneurysm Haemodynamics Altered by Wall Movement DOI : 10.3390/bioengineering11030269
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2024
Evaluating the Impact of Domain Boundaries on Hemodynamics in Intracranial Aneurysms within the Circle of Willis DOI : 10.3390/fluids9010001
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2023
Reinforcement learning for patient-specific optimal stenting of intracranial aneurysms DOI : 10.1038/s41598-023-34007-z
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2023
Large-scale parallel topology optimization of three-dimensional incompressible fluid flows in a level set, anisotropic mesh adaptation framework DOI : 10.1016/j.cma.2023.116335
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2023
Deep learning model for two-fluid flows DOI : 10.1063/5.0134421
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2022
A review on deep reinforcement learning for fluid mechanics: An update DOI : 10.1063/5.0128446
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2022
Single-step deep reinforcement learning for two- and three-dimensional optimal shape design DOI : 10.1063/5.0097241
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2022
Anisotropic adaptive body-fitted meshes for CFD DOI : 10.1016/j.cma.2022.115562
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2022
Deep learning model to assist multiphysics conjugate problems DOI : 10.1063/5.0077723
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2021
A review on deep reinforcement learning for fluid mechanics DOI : 10.1016/j.compfluid.2021.104973
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2021
Stabilized finite element method for incompressible solid dynamics using an updated Lagrangian formulation DOI : 10.1016/j.cma.2021.113923
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2021
Direct shape optimization through deep reinforcement learning DOI : 10.1016/j.jcp.2020.110080
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2021
Deep reinforcement learning for the control of conjugate heat transfer DOI : 10.1016/j.jcp.2021.110317
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2021
Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows DOI : 10.1103/PhysRevFluids.6.053902
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2021
Robust deep learning for emulating turbulent viscosities DOI : 10.1063/5.0064458
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2021
Viscoplastic dam-breaks DOI : 10.1016/j.jnnfm.2020.104447
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2020
Anisotropic boundary layer mesh generation for reliable 3D unsteady RANS simulations DOI : 10.1016/j.finel.2019.103345
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2019
Conservative and adaptive level-set method for the simulation of two-fluid flows DOI : 10.1016/j.compfluid.2019.06.022
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2019
Capillary, viscous, and geometrical effects on the buckling of power-law fluid filaments under compression stresses DOI : 10.1016/j.compfluid.2019.06.014
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2017
Numerical investigation of a viscous regularization of the Euler equations by entropy viscosity DOI : 10.1016/j.cma.2016.12.010
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2017
FEnics-HPC: Coupled multiphysics in computational fluid dynamics DOI : 10.1007/978-3-319-53862-4_6
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2014
Analysis of a fractional-step scheme for the P1 radiative diffusion model DOI : 10.1007/s40314-014-0186-z
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2012
Convergence of a finite volume scheme for the convection-diffusion equation with L1 data DOI : 10.2307/23268048
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2008
A Finite Volume Stability Result for the Convection Operator in Compressible Flows . . . and Some Finite Element Applications
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2008
A Monotone Scheme for the k−ε RNG Model
PhD supervision
- 2025 Advanced simulation of polymer quenching for sustainable aerospace manufacturing CHAKIB Amal
- 2024 Spatial qualification of satellite ceramic components using numerical simulation of thermal shock tests. ABDEL GHANI Hasan
- 2023 Numerical modeling and simulation of dewetting for Newtonian and viscoelastic fluids HERTEL Nicolas
- 2022 A partitioned fluid–structure interaction numerical framework for the simulation of intracranial aneurysms with hyperelastic wall behavior RBAH Abdelilah
- 2021 Analysis of the impact of arterial wall motion on blood flow in intracranial aneurysms through fluid-structure interaction simulations GOETZ Aurèle
- 2021 Advanced Hemodynamic Modeling and Simulation of Flow-Diverter Stents in the Treatment of Intracranial Aneurysms JEKEN RICO Pablo
- 2020 Topological Optimization of High-Efficiency Heat Exchangers Using the Level-Set Method and Anisotropic Mesh Adaptation ABDEL NOUR Wassim
- 2020 Strategies for flux correction in continuous finite element approximations of the compressible Euler equations on unstructured meshes DEVOS Thibaut
- 2019 A posteriori error estimation and adaptive control of iterative finite element solvers with mesh adaptation: application to the quenching process. MEDGHOUL Ghaniyya
- 2019 Numerical and parallel modeling of an anisotropic adaptive mesh for industrial quenching applications EL AOUAD Sacha
- 2018 An adaptive immersed mesh method (AIMM) for fluid-structure interaction (FSI) NEMER Ramy
- 2018 Rapid and flexible heat transfer by radiation for sintering applications GERARD Rémi
- 2018 New modeling framework for interface capture and boiling for industrial cooling BOUBAYA Ali-Malek
- 2017 Optimal resolution of iterative solvers with anisotropic adaptive meshing MANZINALI Gabriel
- Application de l’Apprentissage Profond à la Prédiction et à la Modélisation des Écoulements de Fluides Multiphysiques George El Haber