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of the vibrational energy. This project is intended to perform numerical analysis and modelling aimed at the optimisation and development of effective friction dampers. The research studies on friction damping will be
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performance of AI models for fall detection. The research will combine experimental studies on different floor systems, finite element simulations of vibration propagation, and AI-based signal analysis
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, finite element simulations of vibration propagation, and AI-based signal analysis to establish a physics-informed understanding of the relationship between structural behaviour and fall detection accuracy
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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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are looking for a highly motivated individual with a strong background in civil/structural/mechanical engineering with experience and interest in structural dynamics, vibrational analysis, train-track-bridge
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(e.g. locking oscillators to a common source) but also hybrid methods Analysis of target Signal-to-Noise Ratio (SNR) achievable through effective signal synchronisation against use cases
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knowledge gaps. The project involves both linear and nonlinear dynamics modelling and analysis, as well as experimental testing. An equivalent test structure will first be constructed in the vibration
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issues in the engineering analysis and design of floating wind applications. Over time, these subsea cables become coated with soft and hard biofouling – marine organisms that increase drag, weight and
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that connect floating wind turbines to the seabed remain one of the challenging issues in the engineering analysis and design of floating wind applications. Over time, these subsea cables become coated with soft
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determine the mass flowrate based on the phase shift of vibration of one or more flow tubes. However, the coupling effect of flow performance and vibration of structure, as the underlying mechanism of CMF