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adverse events in the operating room. An existing multi-agent simulator is already in place, but this thesis aims to improve it in several ways. The first improvement involves establishing a connection
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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wide range of scientific skills, with each supervisor covering a specific area of expertise (DFT and Thermodynamics, Kinetics, Molecular Dynamics and ML potentials). The candiadte will contribute to a
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matrix could better resist to fire than the ordinary concretes [9,10], however no numerical simulation has been carried out to confirm. Description of the work: The PhD thesis includes two phases
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programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key
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mostly focus on the WP1 of the MULTI-STEP project lying on atomic scale simulations. The main objective of this WP is to provide deviatoric stress-dependant phase diagram for both titanium and silica. In
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property simulations of ammonia–hydrogen mixtures. It will leverage multiphysics Direct Numerical Simulations (DNS) with detailed chemical kinetics and coupled thermal radiation to improve chemical
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the results of numerical simulations (ideliazed and in a cosmological context) with analytical models that they will develop, in order to understand the detailed physics of bar formation and evolution in
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will be modelled by analytical and numerical approaches. Existing analytical approaches will be used as a tool to describe the behaviour of fire exposed TRC in tension, while numerical simulations will
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of an external magnetic field into the phase-field model and to simulate the microstructural evolution for different cooling rates. - Phase-field modeling of the phase transition in the Fe-Ni alloy. The selected