PhD opportunities

HPC and digital twins in metallurgy - 3D front-tracking modeling of evolving interface networks

Thesis proposal

Area of expertiseMathématiques numériques, Calcul intensif et Données
Doctoral SchoolSFA - Sciences Fondamentales et Appliquées
SupervisorM. Marc BERNACKI
Research unitCentre for material forming
Starting dateOctober 1st 2021
KeywordsDigital twins, HPC, Computational Metallurgy, Interface networks, Front tracking, ToRealMotion algorithms
AbstractContext and goals of the PHD
The in-use properties and durability of metallic materials are strongly related to their microstructures, which are themselves inherited from the thermomechanical treatments. Hence, under-standing and predicting microstructure evolutions are nowadays a key to the competitiveness of industrial companies, with di-rect economic and societal benefits in all major economic sectors (aerospace, nuclear, renewable energy, and automotive industry).

Multiscale materials modeling, and more precisely simulations at the mesoscopic scale, constitute the most promising numeri-cal framework for the next decades of industrial simulations as it compromises between the versatility and robustness of physically-based models, computation times, and accuracy. The digimu con-sortium is dedicated to this topic at the service of major industrial companies.

In this context, the efficient and robust modeling of evolving in-terfaces like grain boundary networks is an active research topic, and numerous numerical frameworks exist [1]. In the context of hot metal forming and when large deformation of the calculation domain and the subsequent migration of grain boundary inter-faces are involved, a new promising, in terms of computational cost, 2D front tracking method called ToRealMotion algorithms [2,3] was recently developed.

This PhD will be firstly dedicated to developing a 3D ToReal-Motion algorithm. If the extension of the data structure will be quite natural, the 3D meshing/remeshing procedures/operators enabling to preserve valid data structure, a good quality of the finite element mesh while remaining frugal in terms of numerical cost remain to be invented.

Moreover, kinetics equations behind the interface networks migra-tion will be enriched to increase the number of modeled physical mechanisms. Finally, a supervised neural network-based remesh-ing strategy will also be developed to improve repetitive and non-optimal operations in the existing remeshing procedures.

The developments will be validated thanks to pre-existing ex-perimental and numerical data concerning the evolution of grain boundary interfaces during recrystallization and related phenom-ena for different materials. They will also be integrated in the DIGIMU® software.
ProfileDegree: MSc or MTech in Applied Mathematics, with excellent academic record.
Skills: Numerical Modeling, programming, proficiency in English, ability to work within a multi-disciplinary team.
FundingFinancement par une entreprise