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Field
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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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objective is to find the best way to embed simple partial differential equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new
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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
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of seaways by a broader spectrum of people than previously appreciated. Welsh connections have been studied in detail for the early medieval period but new excavated and stray-find evidence from the later
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alongside traditional coal fired power stations and nuclear energy generation. Revolutionary changes to power conversion is indispensable if these carbon emissions targets are to be met. The objective is to
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healing, haemostasis promotion and water treatments). The objectives of this project focus on evaluating the antibiofilm efficiencies of different Chitosan derivatives with various polymer sizes and to
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, commissioning cost, lifetime maintenance, replacement and disposal costs and environmental costs also add up to the total evaluated cost of a transformer. Different objective functions in terms of minimisation
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of work throughout the PhD. Project aims and objectives The primary aims of this PhD project are as follows: To investigate how dietary supplementation modulates the gut microbiota and gut permeability
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sensor spoofing. These attacks manipulate input data while maintaining apparent operational normality, potentially leading to unsafe decisions without detection. This project aims to develop a novel