Ongoing research projects
IMMC
Ongoing research projects in iMMC (June 2022)
This a short description of research projects which are presently under progress in iMMC.
Hereunder, you may select one research direction or choose to apply another filter:
List of projects related to: particle methods
 | Implementation of an incompressible hybrid Eulerian-Lagrangian external flow solver Researcher: Philippe Billuart Supervisor(s): Grégoire Winckelmans, Philippe Chatelain Philippe Billuart is working on the development of a new numerical solver that will be able to solve accurately and efficiently any low Mach number external flows. His research is focusing on the hybrid Eulerian-Lagrangian solvers for the incompressible Navier-Stokes equations. Those approaches are based on the decomposition of the computational domain : an Eulerian grid-based solver is used for the computation of the near-wall region, while a Lagrangian vortex method solves the wake region. Even though the coupling of particle methods with Eulerian solvers is not new, only 3D weak coupling were developed so far. This thesis aims to develop a 3D strong coupling ; i.e. a coupling where the Schwarz iterations are not longer required to ensure consistent boundary conditions on each subdomain. As the Schwarz algorithm becomes expensive in 3D, the computational gain in the developed approach should be very significant. |
 | Efficient and scalable frameworks for PDE simulations Researcher: Thomas Gillis Supervisor(s): Philippe Chatelain focuses his research on the development of efficient and scalable computational framework for the simulation of 3D PDEs on massively parallel and heterogeneous architectures. |
 | AI-based control policies towards efficient collective behaviours of flow agents and their application to fish schooling Researcher: Denis Dumoulin Supervisor(s): Philippe Chatelain The principal objective is to shed light on mechanisms allowing anguiliform swimmers to swim very efficiently either on their own or in group. Simulations rely on an unsteady panel method with vortex shedding and on reinforcement learning. |
 | A phase-field discrete elements model applied to granular material Researcher: Alexandre Sac-Morane Supervisor(s): Hadrien Rattez The main goal of the research project is to combine a phase-field modelization with a discrete elements modelization. This new approach is then applied to granular material to investigate the effects of the environment. A model is built and will be calibrated by experiments. |