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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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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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by using commercial software such as Ansys, Abaqus, SolidWorks, etc. Experience in computational fluid dynamics (CFD) modelling or finite element (FE) modelling; Fundamental knowledge in fluid
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techniques — as well as theoretical and computational techniques that may include finite element methods, crystal plasticity theory, damage theory, molecular dynamics and advanced multiscale modelling methods
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. Develop analytical and finite element (FE) models to investigate the extent and sources of nonlinear behaviour in LGSs. 3. Develop novel control strategies to stabilise LGS shape, orbit & attitude
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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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utilise numerical techniques including the finite element method to describe biofluid flow and deformation in the human brain tissue. Parameters are inferred from clinical data including medical images
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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
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fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications
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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