Advanced study into microdamage phenomena in composite materials for hydrogen economy

该项目旨在通过先进的实验和理论相结合的方法，更好地了解高压氢暴露下聚合物复合材料微观损伤背后的控制机制，并开发出预测模型。特别是，将利用合适的机器学习方法来分析从X射线计算机断层扫描(CT)等先进显微镜获得的实验数据，以开发描述材料微损伤过程的机械和数据驱动相结合的建模方法。这将为改进高压氢环境中复合行为的理论和预测模型奠定基础。这项研究还旨在通过向我们的工业合作者提出有用的指导方针来提供非学术影响，帮助我们理解复合材料在高压气体环境下的微损伤的临界状态。因此，这将允许开发不那么保守和更可持续的设计协议，以帮助开发未来使用聚合物复合材料的轻型氢气基础设施。

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.