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Field
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence
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innovation and find diverse applications across industries such as aerospace, energy, and automotive. Among its various techniques, wire-arc directed energy deposition (WA-DED) stands out as a highly promising
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hardware design, and build in fault detection and correction to ensure secure, efficient operation in space systems. The outcome will be a high-performance, fault-tolerant Falcon implementation, enhancing
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resilient to future change. This project will evaluate potential future land use configurations in several countries, exploring where and how biomass production can support multiple objectives for a
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environments—such as fleets with multiple aircraft types. Objectives Objective 1: Map current data types, structures, and interoperability challenges to build a detailed "as-is" understanding of current
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of the challenges is fault detection and diagnosis of bearings subject to low (rotational) speed. As vibration/acoustic signals generated by the faults of low-speed bearings are very weak and often covered by strong
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the project. Project Objectives Characterise the surface properties of reclaimed carbon and glass fibres from different sources and with varying processing histories. Investigate suspension behaviour, including
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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Bayesian inference framework for identifying complex aerospace systems combining with limited experimental data. It can be also used to quantify uncertainties from experimental testing, significantly