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for validation of CFD results. Implement novel unsteady CFD and next generation in-house AI based design tools validated by the gathered experimental data on GKN resources with tight collaboration
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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candidate with a strong background in computational fluid dynamics (CFD) and specialized expertise in hemodynamics associated with coronary artery disease (CAD). The ideal candidate will hold a PhD in
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model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas film flow within the microscopic seal gap. Couple CFD with Structural Models: Study the fluid-structure
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. Collectively, the team holds expertise in the clinical management and treatment of IAs, biology of the IA wall, patient-specific CFD modeling, and biomechanics of IA walls. The faculty member will contribute
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: reduced-order models (ROMs) and input-output models derived from high-fidelity Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter
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bio materials and porous materials PhD student candidate 2 with background in computer science, AI, machine learning or related fields with the experience in CFD, ANSYS, COMSOL The successful candidates
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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universities, research institutes, and industrial partners, will provide interdisciplinary training spanning chemical and mechanical engineering, computational fluid dynamics (CFD), experimental combustion