Ongoing research projects

IMMC

Ongoing research projects in iMMC (December 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:

Biomedical engineering

Computational science

Civil and environmental engineering

Dynamical and electromechanical systems

Energy

Fluid mechanics

Processing and characterisation of materials

Chemical engineering

Solid mechanics


Research direction:
Listed keyword:
Other keyword:
Division:
Supervisor:

List of projects related to: finite elements




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.



Curvilinear mesh adaptation
Researcher: Amaury Johnen
Supervisor(s): Jean-François Remacle

graduated as a physician engineer at the University of Liège (Belgium) in 2011. Then he accomplished a PhD in the topic of quadrangular mesh generation and cuvilinear mesh validation, under the supervision of professor Christophe Geuzaine. He started a postdoctoral research in January 2016 under the supervision of professor Jean-François Remacle for working on curvilinear mesh generation, hex-dominant mesh generation and mesh validation.



BIODEC, STOCC
Researcher: Audrey Favache
Supervisor(s): Thomas Pardoen

obtained a PhD degree in the domain of process control in 2009 at Université catholique de Louvain (Belgium), after having graduated there as chemical engineer in 2005. Since then, she is working as a "senior" researcher on several applied research projects in collaboration with the industry in the domain of mechanics of materials. More particularly, she is interested in the link between the mechanical properties of the individual components of a complex system and the global mechanical response of this system. She applied this approach to the framework of tribology and contact mechanics for understanding the scratch resistance of coatings and multilayered systems. Her work covers both experimental aspects and finite element simulations.



3D crossfield generation for multibloc decomposition
Researcher: Alexandre Chemin
Supervisor(s): Jean-François Remacle

The aim of the project is to realize multibloc decomposition of 3D volumes in order to generate full hex meshes. Nowadays, this kind of decomposition is done by hand. The purpose of this work is to be able to do it in an automatic way. In order to reach this objective, we are generating 3D crossfields in this volume to locate singular points and automatize the decomposition.



Improving the properties of glass fiber reinforced acrylic thermoplastic resin based composites
Researcher: Sarah Gayot
Supervisor(s): Thomas Pardoen

For the manufacturing of continuous fiber reinforced thermoplastic composites (CFRTP), certain monomers can be infused through glass fabric and then polymerized in situ, in order to make a thermoplastic composite part. However, defects - e.g. porosity - can occur in the material, due to the thickness of the laminates and the shrinkage of the resin matrix during polymerization. Such phenomena must be understood, as well as their effects on the mechanical properties of the final composite part.

The originality of this work lies in the very nature of the polymeric matrix used for manufacturing the composite parts, which is thermoplastic instead of thermoset. Little is known about the behaviour of such thermoplastic composites, especially at a microscopic scale. During this PhD, we will try to understand how defects occurring in the material can influence the structural properties of the CFRTP, and we will try to mitigate (or at least control) the incidence of such defects. This will imply a better knowledge of how usual characterisation techniques can be applied from thin to thick composite parts. In particular, digital simulation will be used so as to predict the properties of thick composite parts from those of thinner samples.



Optimization of tensegrity bridges based on morphological indicators
Researcher: Jonas Feron
Supervisor(s): Pierre Latteur

Tensegrity structures are composed of struts and tendons in such way that the compression is “floating” inside a net of tension in a stable self-equilibrated state. Although tensegrity forms have inspired artists and architects for many years, there exist very few real construction projects across the world. The main reasons are, among others, the complex construction processes and the lack of design guidelines. This research, performed in collaboration with the company BESIX, aims at proving the feasibility of a first pure tensegrity bridge around the world.
When the structure is externally loaded, large displacements occur and require non-linear calculation before reaching an equilibrium. Indeed, in tensegrity structures more than in conventional ones, form and forces are intrinsically correlated. This phenomenon is due to their intern mechanism, unless appropriate pre-stressing is applied. An allowable stiffness can be possible, but at a certain material cost, which in turn justifies the relevance of the optimization of the weight.
While designing a tensegrity structure, optimization and form finding are often great challenges. Indeed, the large amount of parameters (span, height, shape, cross sections, materials, loads, pre-stress, etc) makes the search for the structure with the best performances cumbersome. A solution to this problem is to reduce the number of degrees of freedom to consider, by grouping them into dimensionless numbers, the morphological indicators.
In 2014, R.E. Skelton et al were pioneers in using a similar approach for optimizing planar tensegrity bridges uniformly loaded. In 2017, P. Latteur et al adapted the morphological indicators methodology, used so far to optimize mainly trusses and arches, to 3D non-linear and pre-stressed lattice structures such as tensegrity structures. In 2019, J. Feron et al used this methodology to investigate the performances of different 3D forms of uniformly loaded tensegrity footbridges.
This research focus on the required checks to ensure the practicality, the constructability and the economical and structural efficiency of a pure tensegrity footbridge thanks to non linear finite element analysis, experimental validation, parametric design, prestress optimization and dynamic behavior assessment



Torsional Response of RC U-shaped Walls
Researcher: Ryan Hoult
Supervisor(s): Joao Saraiva Esteves Pacheco De Almeida

Although RC U-shaped walls are abundantly embedded within the RC building stock internationally, there is currently no experimental evidence for the capacity of RC U-shaped walls subjected to either pure torsion or a combination of flexure and torsion. This research experimentally assesses the torsional behaviour and capacity of three large-scale reinforced concrete U-shaped walls. This research is important for developing simple design guidelines that can be implemented in future building codes.



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.



2-phase CFD simulations of electrolyte-bubble interactions during alkaline water electrolysis
Researcher: Kevin Van Droogenbroek
Supervisor(s): Joris Proost

In today’s world, concern is growing about the future of energy. Despite very ambitious international climate goals by 2050, global energy-related carbon dioxide (CO2) emissions keep increasing. In order to tackle this problem, hydrogen (H2) seems to be the right solution since it is a way to produce, store, move and use energy in a clean way. However, 95% of the actual hydrogen production is made of grey hydrogen, e.g. H2 produced from fossil energies, which leads to high CO2 emissions in the atmosphere. One way to decarbonise this energy vector is to produce green hydrogen by means of renewable energies (solar panels, wind turbines, etc). This is where my research project funded by the Walloon region comes in, focusing on the production of green hydrogen by alkaline water electrolysis (AWE).

In general, AWE is characterised by the use of two planar electrodes separated by a certain distance and operating in a liquid alkaline electrolyte solution (e.g. KOH, potassium hydroxide). However, the efficiency of the process can be improved by the use of 3D electrodes in a zero-gap cell configuration. This configuration is the one that will be used in the scope of this research and it is depicted in Figure 1. The chemical reactions taking place at the cathode and at the anode are also highlighted.

More specifically, the work will consist in the fluid mechanical modeling of liquid and gaseous flows within alkaline electrolysis cells filled with 3D porous structures. The study of liquid electrolyte flow and of gaseous hydrogen bubble formation and escape will allow to optimise the performance of the electrolyser. Computational Fluid Dynamics (CFD) is a powerful numerical tool that will be used during this project to determine the optimal flow parameters required to homogenise the electrolyte flow (to take advantage of the full specific area provided by the electrodes) while favouring hydrogen bubbles removal from the electrolysis cell (to avoid bubble entrapment within the complex 3D structure).

As an example, the added value of a numerical simulation for a better understanding of the electrolyte flux distribution within an empty cell (e.g. without 3D structure) is shown in Figure 2. The velocity field of the electrolyte (in m/s) was simulated on the OpenFOAM software. Note that the geometry of the cell corresponds to the one of the pilot electrolyser used at UCLouvain (see Figure 3).



SLIM-G : GPU-accelerated SLIM
Researcher: Miguel De Le Court
Supervisor(s): Vincent Legat

I am developing a GPU version of the SLIM ocean model in order to significantly increase its performance, which unlocks previously unreachable resolutions.

Most current ocean models still use the CPU for all the computations, which makes them comparatively slow, and unable to use the next generation of supercomputers such as LUMI. Among the ocean models that are accelerated on the GPU, all of them either use finite differences, which lacks flexibility in the meshes, or finite volumes, which are often low order methods. Contrary to that, SLIM uses the discontinuous Galerkin Finite elements method, which is known for its low diffusivity in advective processes and maps very well to the massively parallel architecture of the GPU.

The current GPU version is still incomplete, but shows speedups of a factor ranging from 50x to 120x faster than a CPU. (R7 2700X vs RTX2080).