Ongoing research projects
IMMC
Ongoing research projects in iMMC (June 2023)
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: multi-body systems
 | WholeTrack Researcher: Nicolas Docquier Supervisor(s): Paul Fisette The project aims at improving railway track lifecycle by improving its components such as the ballast, the sleeper, elastic pads, ... It consists in developing computer models coupling multi-body system dynamics (MBS) and granular modelling method (the discrete element method, DEM). Full scale experiments are conducted in parallel to validate the numerical models and assess the developed solutions. |
 | Crane dynamis (CRAMIC) Researcher: Olivier Lantsoght Supervisor(s): Paul Fisette Historically, the cranes of the ports were assumed to be static or cyclical but, because of the increases in speed and loads, they are becoming more and more dynamic. As a result, load on the rail tracks is increasing and negative effects occurs (such as uncontrolled motion, track deformation…). As one of the partners of CRAMIC global project, through multibody and granular analysis of the system crane-railway. On one side, we focus on identifying and studying the present dynamic effects, participating in developing new track technologies and helping monitoring cranes to organize a future maintenance. On the other side, we focus on the interaction between sleepers and ballast, participating in creating new sleeper geometries. |
 | Modèle hybride multi- échelle pour l’ étude rh éologique des solutions de macromolécules Researcher: Nathan Coppin Supervisor(s): Vincent Legat graduated in physical engineering at Université Catholique de Louvain in 2018 and is currently pursuing a PhD under the supervision of Prof. Vincent Legat. The goal of his thesis is to study the performance of the MigFlow Software using applications that require the management of frictional contacts. |
 | 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. |