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addresses the "calibration problem" in particulate continuum models and particle simulations. Specifically, it focuses on developing robust methodologies for selecting and parameterising contact models, a
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Description: Accurate battery State of Health (SOH) estimation is vital for electric vehicle safety and longevity. Current models often fail to balance accuracy with computational efficiency. Collaborating with
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and toxicity performance make them strong candidates for safety‑critical applications in aerospace, rail, automotive and battery technologies. However, current PFA systems suffer from brittleness
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multiphysics models to investigate aquifer-based compressed air energy storage (CAES) systems. The research will involve coupling fluid flow, heat transfer, geomechanics, and potentially reactive transport
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: how can physics-based flow modelling be coupled with advanced optical sensing to infer methane emission rates accurately and with quantified uncertainty? The project will pursue three core objectives
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environmental change. Current models often treat phenotypes as fixed traits, overlooking the developmental processes through which organisms construct their phenotypes, creating a key “phenotypic gap” in
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that you apply early as the advert may be removed before the deadline. This PhD project aims to develop a virtual tabletting laboratory by creating computational models that capture the multiscale mechanics
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This PhD studentship, based at the University of Exeter's Penryn Campus (Cornwall), offers an opportunity to conduct research at the intersection of wind energy, power systems, and advanced control
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develop physics‑informed neural surrogates to support real‑time digital‑twin CFD for offshore wind turbines. Key objectives include: Designing PINN and operator‑learning models that enforce incompressible
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these internal conditions vary across space and time. Depending on the student’s interests and skills, the project may involve a combination of: • Experimental studies using model plant species to examine root