Advanced study into microdamage phenomena in composite materials for hydrogen economy

This project aims to understand better the controlling mechanisms behind microscopic damage and develop a predictive model for polymer composites subject to high-pressure hydrogen exposure, by combining advanced experiments with theory. Particularly, a suitable Machine Learning approach will be utilized to analyse experimental data obtained from advanced microscopy such as X-ray computed tomography (CT), to develop a combined mechanistic and data-driven modelling methodology describing the material microdamage process.

This will form the basis for an improved theory and predictive models of composite behaviour in high-pressure hydrogen environments.

This study also aims to provide non-academic impact by proposing useful guidelines to our industrial collaborator about understanding critical states of microdamage in composite materials subject to high-pressure gaseous environments. Consequently, this will allow development of less conservative and more sustainable design protocols that will assist development of future light-weight hydrogen infrastructure with polymer composite materials.