Early-stage failure prediction in fusion materials using machine learning

This project will leverage a database of high-resolution surface displacement measurements to learn state space representations of the kinematic data and pattern recognition techniques to reveal early-stage fingerprints for early-stage damage.

phd researcher - Josh Lee supervisor - Prof Chris Race

Early stage failure prediction in fusion materials using machine learning

Project supported by UKAEA at The University of Sheffield