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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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-cycle fatigue. The research methods are based on both small-scale and full-scale experimental testing and on Finite Element Modelling. Are you motivated to take a step towards a doctorate and open
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Principal Investigator (PI) or Co-Principal Investigator (Co-PI) on research studies. Perform non-linear, dynamic, finite element analysis (FEA) and design for various research studies involving low- to high
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4-year D.Phil. studentship Supervisors: Dr Simone Falco, Prof Daniel Eakins Classic finite elements approach (FEA) approximate the shape of the model using elements with planar faces, therefore
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Finite Element Model of the Larva Body: Utilise existing Drosophila larva CT-scan data to segment components such as the cuticle, muscles, and mouth hook. Implement finite element simulations within
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of materials mechanics, e.g., plasticity, porous plasticity, crystal plasticity and damage mechanics. Knowledge of micromechanical modelling. Knowledge of non-linear finite element methods. Knowledge of FFT
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code based on Modified Newtonian aerodynamics and a coupled, nonlinear thermo-structural finite element solver. Supervisors: Professor Matthew Santer, Dr. Paul Bruce. Learning opportunities: You will
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of building and structural concepts through the development of AI-enhanced Finite Element Method (FEM) tools. It includes implementing FEM-based systems capable of proposing innovative structural forms
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pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
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upcycling of spent metal oxide cathodes, particularly, high Ni-containing oxides, through chemical-mechanical approaches, ionothermal/molten salt methods, etc. Project 2 (2 PhD students): Direct Recycling