Intelligent Monitoring of Hydrogen Energy Systems for Zero Emissions and Predictive Maintenance

This PhD research aims to pioneer real-time and autonomous condition monitoring systems for operational Hydrogen Energy components (pipelines/pressure vessels/valves). Integrating Acoustic Emission (AE), Vibration and ultrasonic sensing, the project targets rapid identification/characterisation of damage, including leakage/impact-damage/cracks/corrosion/localized-inhomogeneity, under variable loading and operating conditions. Through rigorous experimental, analytical, and computational efforts, including Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) simulations, Multiphysics modeling, and Bayesian data assimilation, this interdisciplinary initiative seeks to develop intelligent condition monitoring technologies. Leveraging edge computing-based smart sensing technologies, the project aims to enhance safety, reduce maintenance costs, and redefine operational practices in the energy sectors.