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melting methodology creates challenges due to limited in-situ thermal control that can generate unwanted thermal stresses in components, defects such as cracks and limited microstructural control. This PhD
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parameter selection and process optimisation. Previous experience / requirements: Experimental methods, Finite element modelling, computer programming, Manufacturing Please contact Dr Hassan Ghadbeigi
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parameter selection and process optimisation. Previous experience / requirements: Experimental methods, Finite element modelling, computer programming, Manufacturing Funding Notes Please note that this
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Experience with the use of Finite Element Methods in modelling acoustic problems (assessed at: Application form/Interview) Essential Application and Interview Experience with Python or Matlab or any other
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enable meaningful acceleration of the qualification processes. This research will focus on the development of melt pool physics to the predict surface roughness and microstructure of additively
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experience in use of Finite element analysis and its application, familiarity with electric machines Contact: h.ghadbeigi@sheffield.ac.uk, m.i.boulis@sheffield.ac.uk Keywords: Manufacturing, Sheet forming
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mechanical testing, Digital Volume Correlation, and nanoindentation Lead the microstructural assessment of children bone tissues Collaborate with the ChildBone project team to inform and validate the outputs
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Application/Interview Strong background in semiconductor device design and/or simulation, including photolithographic mask layout Essential Application/Interview Experience of 3D finite element modelling (FEM
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-based micro-finite element (microFE) models of the mouse alveolar bone can be used to evaluate accurately the bone stiffness, bone strength and local deformation, as compared against state-of-the-art
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of developing novel computational frameworks that seamlessly integrate machine learning techniques with established methods in computational mechanics, such as the Phase-field Finite Element Methods. Potential