With six ERC grants awarded since 2016, The Institute of Mechanics, Materials, and Civil Engineering (iMMC) is a leading international center for research in engineering.听
听
(HA-)PI (2023-2028)
Thomas Pardoen is the (HA-)PI of an ERC Advanced Grant.
The vision of the project, named HAPI(*), is that the fracture resistance of metallic components can be enhanced by selecting and/or controlling the optimum plate thickness in thin-walled applications and of constituents of thick laminates.
HAPI is at the interface between solids mechanics & metallurgy, combining processing, experiments and numerical simulations.
(*) Acronym HAPI refers to three renown scientists: John Hutchinson (Harvard U.), Tony Atkins (U. Reading) and Andr茅 Pineau (Ecole des Mines de Paris)
X-MESH (2023-2029)
X-MESH is an innovative approach that aims to overcome a major difficulty associated with engineering analysis: by providing a revolutionary way to track physical interfaces in finite element simulations using extreme deformation of the meshes.
The key idea is to allow elements to deform up to zero measure. For example, a triangle can deform to an edge or even a point. This idea is rather extreme and totally revisits the interaction between the meshing community and the computational community, who, for decades have striven to interact through beautiful meshes.
Six areas in fluid and solid mechanics as well as heat transfer are targeted. Interfaces will be either material, i.e., attached to particles of matter (the interface between two immiscible fluids or the dry interface in a wetting and drying model) or immaterial, i.e. migrating through the material (solidification front, contact front, yield front or crack front).
Advances are expected from this X-MESH method in the following engineering fields: safety design and maintenance, manufacturing processes, coastal engineering, energy efficiency, ocean modeling, to name but a few.
CO2LIFE (2018-2023)
The continued increase in the atmospheric concentration of CO2 due to anthropogenic emissions is leading to significant changes in climate, with the industry accounting for one-third of all the energy used globally and for almost 40% of worldwide CO2 emissions. Fast actions are required to decrease the concentration of this greenhouse gas in the atmosphere, value that has currently reaching 400 ppm. Among the technological possibilities that are on the table to reduce CO2 emissions, carbon capture and storage into geological deposits is one of the main strategies that is being applied. However, the final objective of this strategy is to remove CO2 without considering the enormous potential of this molecule as a source of carbon for the production of valuable compounds. Nature has developed an effective and equilibrated mechanism to concentrate CO2 and fixate the inorganic carbon into organic material (e.g., glucose) by means of enzymatic action. Mimicking Nature and take advantage of millions of years of evolution should be considered as a basic starting point in the development of smart and highly effective processes. In addition, the use of amino-acid salts for CO2 capture is envisaged as a potential approach to recover CO2 in the form of (bi)carbonates.
The project CO2LIFE presents the overall objective of developing a chemical process that converts carbon dioxide into valuable molecules using membrane technology. The strategy followed in this project is two-fold: i) CO2 membrane-based absorption-crystallization process on basis of using amino-acid salts, and ii) CO2 conversion into glucose or salts by using enzymes as catalysts supported on or retained by membranes. The final product, i.e. (bi)carbonates or glucose, has a large interest in the (bio)chemical industry, thus, new CO2 emissions are avoided and the carbon cycle is closed. This project will provide a technological solution at industrial scale for the removal and reutilization of CO2.
WakeOpColl : LEARNING AND COLLECTIVE INTELLIGENCE FOR OPTIMIZED OPERATIONS IN WAKE FLOWS (2017-2023)
Physics dictate that a flow device has to leave a wake or the signature of it producing sustentation forces, extracting energy, or simply moving through the medium; these flow structures can then impact negatively or favorably another device downstream.Wake turbulence between aircraft in air traffic and wake losses within wind farms are prime examples of this phenomenon, and incidentally constitute pivotal challenges to their respective fields of transportation and wind energy.
These are highly complex and unsteady flows, and distributed control based on affordable wake models has failed to produce robust schemes that can alleviate turbulence effects and achieve efficiency at the scale of the system of devices.
This project proposes an Artificial Intelligence and bio-inspired paradigm for the control of flow devices subjected to wake effects.
To each flow device, we associate an intelligent agent that pursues given goals of efficiency or turbulence alleviation. Every one of these flow agents now relies on machine-learning tools to learn how to make the right decision when confronted with wake or turbulent flow structures.
At a system level, we employ Multi-Agent System and Distributed Learning paradigms. Based on Game Theory, we build a system of interactions that incite the emergence of collaborative behaviors between the agents and achieve global optimized operation among the devices.
We claim that the design of a system that learns how to control the flow, is simpler than the design of the control scheme and will yield a more robust scheme. The learning of formation flying among aircraft and of wake alleviation between wind turbines will constitute our study cases. The investigation will essentially be carried by means of large-scale numerical simulations; such simulations will produce the first ever realizations of self-organized systems in a turbulent flow. We will then apply our learning frameworks to a small-scale wind farm.
ALUFIX - Damage healing strategies for durable light metals (2017-2022)
Aude Simar obtained an ERC starting grant 2016
The ALUFIX project proposes an original strategy for the development of aluminium-based materials involving damage mitigation and extrinsic self-healing concepts exploiting the new opportunities of the solid-state friction stir process. Friction stir processing locally extrudes and drags material from the front to the back and around the tool pin. It involves short duration at moderate temperatures (typically 80% of the melting temperature), fast cooling rates and large plastic deformations leading to far out-of-equilibrium microstructures.
The idea is that commercial aluminium alloys can be locally improved and healed in regions of stress concentration where damage is likely to occur. Self-healing in metal-based materials is still in its infancy and existing strategies can hardly be extended to applications. Friction stir processing can enhance the damage and fatigue resistance of aluminium alloys by microstructure homogenisation and refinement. In parallel, friction stir processing can be used to integrate secondary phases in an aluminium matrix.
In the ALUFIX project, healing phases will thus be integrated in aluminium in addition to refining and homogenising the microstructure. Along the road, a variety of new scientific questions concerning the damage mechanisms will have to be addressed.
Principle of Friction Stir Processing (FSP)
HEXTREME : HEXAHEDRAL MESH GENERATION IN REAL TIME (2016-2021)
Over one million finite element analyses are preformed in engineering offices every day and finite elements come with the price of mesh generation.
This proposal aims at creating two breakthroughs in the art of mesh generation that will be directly beneficial to the finite element community at large.
The first challenge of HEXTREME is to take advantage of the massively multi-threaded nature of modern computers and to parallelize all the aspects of the mesh generation process at a fine grain level.
Reducing the meshing time by more than one order of magnitude is an ambitious objective: if minutes can become seconds, then success in this research would definitively radically change the way in which engineers deal with mesh generation.
This project then proposes an innovative approach to overcoming the major difficulty associated with mesh generation: it aims at providing a fast and reliable solution to the problem of conforming hexahedral mesh generation.
Quadrilateral meshes in 2D and hexahedral meshes in 3D are usually considered to be superior to triangular/tetrahedral meshes. Even though direct tetrahedral meshing techniques have reached a level of robustness that allow us to treat general 3D domains, there may never exist a direct algorithm for building unstructured hex-meshes in general 3D domains.
In HEXTREME, an indirect approach is envisaged that relies on recent developments in various domains of applied mathematics and computer science such as graph theory, combinatorial optimization or computational geometry.
The methodology that is proposed for hex meshing is finally extended to the difficult problem of boundary layer meshing. Mesh generation is one important step of the engineering analysis process. Yet, a mesh is a tool and not an aim.
A specific task of the project is dedicated to the interaction with research partners that are committed to beta-test the results of HEXTREME. All the results of HEXTREME will be provided as an open source in Gmsh.