HPC and digital twins in metallurgy – 3D front-tracking modeling of evolving interface network based on optimized mesh adaptation algorithms
CEMEF, MINES ParisTech, Sophia Antipolis
Context and goals
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 direct 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 numerical 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 consortium is dedicated to this topic at the service of major industrial companies.
In this context, the eﬀicient and robust modeling of evolving interfaces like grain boundary network is an active research topic, and numerous numerical frameworks exist . In the context of hot metal forming and when large deformation of the calculation domain and the subsequent migration of grain boundary interfaces are involved, a new promising 2D front tracking method, called ToRealMotion algorithms [2,3] was recently developed.
This PhD will be firstly dedicated to developing a 3D ToRealMotion 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 network migration will be enriched to increase the number of modeled physical mechanisms. Finally, a supervised neural network-based remeshing strategy will also be developed to improve repetitive and nonoptimal operations in the existing remeshing procedures.
The developments will be validated thanks to pre-existing experimental and numerical data concerning the evolution of grain boundary interfaces during recrystallization and related phenomena for different materials, and integrated in the DIGIMU® software.
 A. Rollett, G. S. Rohrer, and J. Humphreys, Recrystallization and Related Annealing Phenomena. 3rd Edition, 2017.
 S. Florez, K. Alvarado, and M. Bernacki. A new front-tracking lagrangian model for the modeling of dynamic and post-dynamic recrystallization. Modelling and Simulation in Materials Science and Engineering, In press, 2021.
 S. Florez, K. Alvarado, D. Pino Muñoz and M. Bernacki. A novel highly eﬀicient lagrangian model for massively multidomain simulation applied to microstructural evolutions. Computer Methods in Applied Mechanics and Engineering, 367:113107, 2020.
Degree: 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.
The 3-year PhD will take place in CEMEF, an internationally-recognised research laboratory of MINES ParisTech located in Sophia-Antipolis, on the French Riviera. It offers a dynamic research environment, exhaustive training opportunities and a strong link with the industry. Annual gross salary: about 26k€. She/He will join the Metallurgy μStructure Rheology (MSR) research teams under the supervision of Prof. M. Bernacki and Dr. S. Florez in ”Numerical Mathematics, High Performance Computing and Data” doctoral speciality.