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-mechanical coupling. Understanding of wellbore and casing behavior under thermal load. Desired skills: Finite Element Analysis software: Abaqus, COMSOL Multiphysics, or ANSYS Python (for data analysis
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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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-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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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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treatments, and exposure to gaseous impurities. Using both experimental testing and finite element modelling, you’ll help develop practical guidelines to mitigate hydrogen embrittlement and enable safer, more
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finite element methods, which demand extensive data and are costly, PINNs embed governing physical laws directly into the learning process. This allows effective management of limited and noisy data
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degree in Engineering and have an interest in and/or a good understanding of numerical modelling and testing of structures. Prior knowledge of finite element methods and programming (e.g. C++, Python
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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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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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dynamic analysis of mechanical/robotic systems Ability to use finite element modelling and to simulate complex mechatronics Ability to implement control and kinematics with hardware-in-the-loop Background