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Machine learning-aided multiscale design of porous materials tailored to application-specific, hydro-mechanical performance requirements

Objective

Through continuous interaction between computational fluid dynamics, mechanics of solids, material engineering, and machine learning, with my host, I will develop a novel and computationally efficient method, implemented in open-source software, for the multi-scale design of engineered porous materials (EPMs) that meet user-specified hydro-mechanical functional requirements. This computer-aided approach will accelerate the discovery of EPMs and shorten the time for technology development, and is aimed at EPM design for additive Manufacturing (i.e. 3D-printing). The basic notion of the proposed approach is: (1) to employ a dimensionality reduction techniques to obtain a low-dimensional proxy for the high-dimensional problem of characterizing a porous micro-structure, (2) to develop physics-informed neural networks (PINNs) for scale-specific hydro-mechanical simulation of porous media at the micro (pore) scale, the meso (pore-network) scale, and the macro (Darcy) scale, (3) to employ a physics-based coupling mechanism for scale-specific PINNs, allowing them to form a chain of neural networks for hydro-mechanical structure-property-performance (S-P-P) linkage, and (4) to incorporate a topology optimization algorithm for the multi-scale design of porous media. The focus is on fluid-saturated, poroelastic materials, with special emphasis on biomedical applications that require a defined porous structure, such as meniscus implants and bone scaffolds. I will work on the project at the University of Luxembourg (host institute), in collaboration with the University of Strasbourg (secondment institute).

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2022-PF-01

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Coordinator

UNIVERSITE DU LUXEMBOURG
Net EU contribution
€ 191 760,00
Address
2 PLACE DE L'UNIVERSITE
4365 ESCH-SUR-ALZETTE
Luxembourg
Region
Luxembourg Luxembourg Luxembourg
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Partners (1)