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, several different configurations will be evaluated with your CFD-FEM models and tested at TRL4 (10 kWe) at TU/e to identify the most promising configurations and operation modes, first only for heating
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technology for internal resistive heating of chemical reactors, several different configurations will be evaluated with your CFD-FEM models and tested at TRL4 (10 kWe) at TU/e to identify the most promising
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Dynamics (CFD). This is an exciting opportunity to contribute to cutting-edge research that supports the next generation of sustainable aeroengines. The successful candidate will join a supportive team of
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Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A
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computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly
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, and industrial partners, will provide interdisciplinary training spanning chemical and mechanical engineering, computational fluid dynamics (CFD), experimental combustion diagnostics, and techno
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the viewpoint of the social and philosophical studies of science. About the FairCFD project Over the past seven decades, Computational Fluid Dynamics (CFD) has enabled increasingly efficient industrial processes
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loads, resulting in highly nonlinear coupled hydrodynamic and structural behaviors. High-fidelity CFD-FEA based FSI simulations provide valuable insight but remain computationally expensive for large
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modelling for conversion and sorbent regeneration, in conjunction with another PhD student in the department who will perform CFD modelling and other researchers performing process system modelling within
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other partners within this project. In case a (moving of fixed) bed is chosen, a coarse-grained CFD-DEM model or an Eulerian model will be developed, possibly making use of correlations from particle