Physics-Informed Machine Learning with Applications in Hydrogen Fuel Propulsion Systems

Job description

What are you going to do? Background: The Airbus A380 ZEROe demonstrator aircraft used for testing hydrogen-powered propulsion (source: https://simpleflying.com/rolls-royce-patent-hydrogen-electric-engine-systems-explained/ ) Hydrogen fuel systems are pivotal to the future of aviation, offering a pathway to net-zero carbon emissions. However, their adoption introduces substantial maintenance challenges, as operating with hydrogen involves harsher conditions, stricter safety requirements, and more intricate system behaviour than conventional fuels. Prognostics and Health Management (PHM) can address these challenges by enabling a shift towards condition-based, predictive, and prescriptive maintenance strategies, reducing unplanned downtime, extending component life, and lowering operational costs while improving safety. Realising these benefits, however, depends on the quality of the underlying predictive models, and current approaches face important limitations: purely data-driven models struggle to generalise across operating regimes and require large volumes of representative data, while traditional physics-based models are computationally costly and constrained by simplifying as...