Ongoing research projects
Ongoing research projects in iMMC (August 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: numerical simulation, experimental models
|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.
|Modeling and simulation of water electrolysis.|
Researcher: Christos Georgiadis
Supervisor(s): Joris Proost
The main objective of our work is to develop models for the simulation of 2-phase flows through electrodes. After the initial validation of the model, we will perform a detailed analysis of the flow and electrochemical properties of the system, in conjunction with experimental data. The final objective will be the design of optimal electrode geometries for water electrolysis.
|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.
|Morphological impact of dam-flushing|
Researcher: Robin Meurice
Supervisor(s): Sandra Soares Frazao
An important number of dams worldwide face sedimentation issues, leading to a decrease in their reservoir capacity and hence, many difficulties to properly satisfy to their different functions (e.g. water distribution, flood management, hydroelectricity production). To overcome these problems, we can proceed to dam flushing operations, transporting huge amounts of sediment downstream of the dam. Nevertheless, these operations can be harmful to the environment, the living organisms and the human infrastructures if not properly handled. For that reason, this thesis aims at developing a numerical model capable of accurately predicting the sediment deposition downstream of a dam after flushing operations. In order to do so, several mathematical models shall be implemented, among which a two-phase two-layer model, and laboratory experiments shall be run. The numerical model will then be confronted with the data collected from the experiments. Finally, the model will be tested with real-case data collected in situ near Lyon, France.
|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.
|Carnot batteries as effective sector-coupling systems for heat and power: techno-economic analysis and robust optimisation|
Researcher: Antoine Laterre
Supervisor(s): Francesco Contino
The first concepts of Carnot batteries appeared in the early 2010s. These systems propose to use excess energy from the grid to produce heat and store it in thermal form. This energy can then be returned in the form of electricity through thermal cycles. By their very nature, these “batteries” allow for efficient coupling between electrical and thermal systems, which is an asset regarding the challenges prescribed by the energy transition. For example, they can take advantage of waste heat (< 100°C) to increase their power output to power input ratio to values above 100%. The heat they generate can also be used for other purposes (e.g. industrial).
Theoretical studies to date have shown that this technology has great potential for development. However, they also reveal that the performance can deteriorate severely when certain parameters deviate slightly from the optimal design conditions (i.e. variation of waste heat temperature, of isentropic efficiencies, etc.). In order to evaluate their real potential, this project proposes to integrate, by simulation means, the uncertainty dimension on these parameters to quantify more efficiently the sensitivity of Carnot batteries to them.
To identify the designs that are robust to uncertainty and to evaluate the actual techno-economic performance of these systems, Uncertainty Quantification and Robust Optimisation (optimisation under uncertainty) techniques will be applied. Using metrics such as LCOS, we will assess with more certainty the potential of this technology compared to other storage systems, such as batteries.
|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.