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, this project aims to develop a novel modelling and analysis approach to address the mathematical and technical challenges of the fluid-structure interaction (FSI) mechanisms globally. The successful PhD
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the areas of fluid dynamics, turbulence and net-zero combustion. There is substantial scope for the student to direct the project with the main focus on (i) Generating an advanced Direct Numerical Simulation
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
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on electromagnetic motors, pumps, or compressed air systems. However, motors are often bulky, heavy, and rigid, while fluid systems are typically tethered and inefficient. There is an urgent need for untethered soft
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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Establishment). Recent work by the group (leading to REF 4* rated outputs and several Keynotes) has contributed to bridging the gap between Computational Solid and Fluid Dynamics, with a unified computational
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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Proteins are key biomarkers, indicative of normal biological or pathogenic processes and responses to intervention. Identification and quantification of such molecules in biological fluids is