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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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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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-based solutions (NbS) for water and wastewater treatment. The research will explore sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The
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intelligent systems aim to optimize power usage without compromising performance, employing strategies like power-aware computing and thermal-aware optimization. These systems are crucial in extending
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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investigate strategies to enhance communication security, focusing on resilience against jamming and spoofing attacks. Students will work on designing secure architectures that ensure data integrity and system
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for reconstructing full 3D temperature fields from partial temperature measurements, utilising monitoring techniques deployable in industrial settings. This work will provide critical thermal insights for diagnosing
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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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