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Field
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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. Although there is a clear synergy between fatigue damage and corrosion, most fatigue prognosis models do not explicitly consider the role of the environment, which is usually reduced to obscured fitting
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, a state-of-the-art process-based model for groundwater risk assessment and contaminant transport modeling. By improving predictive modeling of transient contaminant source terms, this research will
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exhibit complex two-dimensional structures whose performance is governed by subtle variations in layer stacking and nanoscale disorder—features that are difficult to resolve with currently available
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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its impact. The PhD will include aerodynamic and CFD modelling of the X-Rotor concept. It may also include wind tunnel testing depending on the candidate recruited. Levilised cost of energy modelling
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. One useful approach to understanding and enhancing this capacity is through community readiness models—frameworks designed to assess how prepared a community is to address a particular public health
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million in losses each year, with landslides during earthquakes leading to over NZ$1 billion in damage for a single event. While landslide susceptibility modelling is an essential tool in risk management