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maintenance. However, current technologies are relatively slow and not capable enough to provide quick performance, diagnostic and prognostic predictions for real time applications. With the rapid development
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on previous research at Cranfield, which has demonstrated the benefits, the project investigates the impact of various porous structures on aerodynamic performance. Focus is placed on the entire incompressible
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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Cranfield’s Advanced Vehicle Engineering Centre is inviting applications to study for a PhD in battery modelling and management for electric vehicles. Several projects are on offer, covering
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experimentation and validation, and machine learning. References of our current/recent work are here: "Automatic Retrieval-Augmented Generation of 6G Network Specifications for Use Cases," IEEE Communications
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water quality, longer operational run times before regeneration for adsorption processes, and associated reductions in operational costs and reduced carbon footprint. The project is an exciting
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. Green Aviation Operations and Infrastructure. Aviation Environmental, Commercialisation & Socio-Economic Aspects. The CDT in Net Zero Aviation is the world’s first Centre of Excellence for Net Zero
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managed to allow for efficient solar energy harvesting. This project will deliver novel methods for modelling and controlling LGS structural dynamics in the extreme orbital environment. The objectives
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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. Green Aviation Operations and Infrastructure. Aviation Environmental, Commercialisation & Socio-Economic Aspects. The CDT in Net Zero Aviation is the world’s first Centre of Excellence for Net Zero