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dynamically combine trusted and opportunistic signals. This project aims to develop versatile benchmarks for assured multi-domain PNT systems with advanced integrity frameworks, enabling rigorous evaluation and
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integrating advanced vision and language transformers with an Explainable AI (XAI) layer, the project aims to create a robust system for accurate threat identification, providing actionable intelligence
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advanced technology and business needs, creating smart monitoring systems, predictive maintenance solutions, and digital twins that solve pressing challenges across healthcare, energy, aviation, and
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research. A novel DRL-based wind turbine control system that dynamically adjusts parameters for improved efficiency and reduced mechanical stress. A Hybrid AI-Predictive Maintenance model that integrates
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This project is sponsored by EPSRC, Cranfield University and a consortium led by ETN global. ESPRC will provide stipend (£22,000 per annum) and cover UK fees. The consortium will provide supervision
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significant weight savings, and improve the overall efficiency of the Hydrogen system, and at the end, of the aircraft. Nevertheless, to deliver those expected benefits, it is absolutely necessary to understand
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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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increasing relevance today due to its ability to bridge the physical, digital, and social domains. CPSS are integral to the modern world, shaping the development of intelligent systems that respond dynamically
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This is a fully funded PhD (fees and bursary) in experimental icing research. Fundamental understanding of droplet impact dynamics is integral to icing. The overall aim of this PhD is to use optical
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The Structural Battery Company, a high-tech manufacturer of EV batteries. Building on Cranfield’s previous APC-funded CERABEV successes using epoxy-based systems with intumescent ceramic phases, this project