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outcomes of this research will be well-validated computational analysis methods to predict failure mode, and quantify defect and damage produced in fibre metal laminate composites. The models can be used
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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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of metrics that aim at quantification of the effect of selected deconstruction methods on the structural reliability of deconstructed elements. As a part of your project you will make a selection of
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-linear, dynamic, finite element analysis (FEA) and design for use in research studies involving low- to high-energy impact events using LS-DYNA and other applicable numerical analysis methods/computer
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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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on mechanics and solid mechanics to masters' level courses such as finite element methods, rigid body dynamics, structural dynamics, and structural dynamics control. The aim of the Division is to be
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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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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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innovative computational approaches, leveraging finite element simulations, AI, and clinical data, to better understand the mechanisms of MR. This aims to improve patient risk stratification and treatment