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Due to unique properties of supercritical CO2 (sCO2), power generation systems using sCO2 as working fluid have many advantages over their counterparts, such as gas turbines and steam turbine power
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technologies. Liquid hydrogen (LH2) is a promising technology for decarbonizing civil aviation, offering zero in-flight CO2 emissions. Its high energy density per unit mass, about three times higher than
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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within the icing group at Cranfield has captured valuable data on droplet splashing, rebound and secondary impingement through experimental research in the vertical icing wind tunnel at Cranfield
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
graphs, and ontologies, the research will help engineers transform unstructured maintenance records into explainable insights. By capturing both technical and experience-based (tacit) knowledge, the system
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unbounded variable and instance sets. In addition, novel approaches such as Physics Informed/Guided Learning allows the learning models to capture the underlying physics/patterns and to generate physically
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loaded in a lab setup. High resolution cameras will be installed to capture the elastic and thermal changes in the material during the loads. Distinct experimental scheme will be designed initially
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of big data might not be possible to be captured by traditional modelling approaches. This implies that mathematical modelling of such data is infeasible. The data-driven modelling approach could resolve