Research project selected under the 2022 call for proposals
Principal Investigator : Frédéric MOMPIOU
Involved Teams :
- CEMES / Physics of Plasticity and Metallurgy, PPM
Type of project : Disruptive Project
Date (start/end) : 2021 – 2024
Mechanical properties of metallic alloys are largely governed by the motion of nano-scale linear defects called dislocations and their interactions with the microstructure.
Hence, understanding dislocation dynamics is of fundamental interest to predict material strength. At CEMES, moving dislocations are directly observed during in-situ TEM straining experiments. Up to date, the dynamics analysis is performed manually, which limits statistical treatments, although a large database of observations is available. Moreover, this approach misses a large amount of information by sampling observations and averaging quantities.
The overall objective of this project is to take benefit of computer vision coupled to deep learning methods to exploit databases in order to construct numerical twins of in-situ observations. We expect from this to retrieve quantitative information that could be further implemented in meso-scale simulations.