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various objectives (model tuning), such as energy indicators (e.g., efficiency, exergy analysis) or parameters affecting investment costs (e.g., heat exchanger pinch, fluid flow rates), in order to build a
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Vacancies PhD position on the design and fabrication of MEMS drag force-based flow and fluid composition sensors Key takeaways In this project, we will combine well-known thermal flow sensing
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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, followed by post-plasma catalysis into C2H4; (2) fully coupled modelling (i.e., plasma fluid dynamics and plasma + catalyst surface chemistry) for plasma-based CH4 conversion with post-plasma catalysis
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Position: Bioprinting next generation functional tissues The field of tissue engineering and bioprinting is continually advancing to develop functional tissue models that more accurately mimic native tissue
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automation Earth processing Computational fluid dynamics Numerical process modelling Rheology Furthermore, the candidate should be motivated to work collaboratively as part of a team. You must have a two-year
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diagrams generated by such models, can be used to explore equilibrium assemblages with respect to the proportion and composition of mineral, melt and fluid phases across a range of geologically-relevant
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hydrodynamics for novel marine vehicles, including large ships and small AUVs and offshore renewable energy systems including offshore wind. You are expected to perform advanced computational fluid dynamics
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to a doctoral degree. The focus of this position is research on hydrodynamic loads and performance of tidal turbines under realistic flow and clearance conditions. Tidal-stream energy offers a
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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method