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Thesis
Home   /   Thesis   /   Hydrodynamic simulations of porous materials for ductile damage

Hydrodynamic simulations of porous materials for ductile damage

Artificial intelligence & Data intelligence Engineering sciences Materials and applications Technological challenges

Abstract

The mechanical behavior of metallic materials under highly dynamical loading (schock) and especially their damage behavior is a topic of interest for the CEA-DAM. For tantalum, damage is ductile : by nucleation, growth and coalescence of voids within the material. Usual ductile damage models have been developed using the simplifying assumption that voids are isolated in the materials. However, recent studies by direct simulations explicitly describing a void population in the material (and experimental observations after failure) have shown the importance of void interaction for predicting ductile damage. Yet, the microscopical mechanisms of this interaction remain little known.
The objective of the PhD is to study the growth and coalescence phases of ductile damage through direct numerical simulations of a porous material undergoing dynamic loading. Hydrodynamic simulations, in which voids are explicitly meshed within a continuous matrix, will be used to study relevant scales of length and time. Monitoring the void population throughout the simulation will provide valuable information on the influence of void interaction during ductile damage. Firstly, the bulk behavior will be compared to the one predicted by usual models of isolated voids, showing the macroscopic effect of void interaction. Secondly, the evolution of the size distribution in the void population will be monitored. The last objective will be to understand microscopic void-to-void interaction. In order to take advantage of the wealth of simulation results, approaches based on artificial intelligence (neural networks on the graph associated with the pore population) will be used to learn the link between a void's neighborhood and its growth.
The doctoral student will have the opportunity to develop their skills in shock physics and mechanics, numerical simulations (with access to CEA-DAM supercomputers), and data science.

Laboratory

Département physique, expériences et modèles
DPEM
DPEM
Paris Sciences et Lettres
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