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Analysis of post-combustion CO2 capture from natural gas power plants using CFD and process co-simulation Department of Mechanical Engineering PhD Research Project Self Funded Prof M Pourkashanian
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? Are you looking for a new and exciting challenge to develop innovative digital tools combining CFD and machine learning to reduce manufacturing-induced deficiencies of ceramics? We have a vacancy for an
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Experience in programming using MPI and high-performance computing Experience in CFD simulations using open-source codes (i.e. Code_Saturne or OpenFoam) will be beneficial but it is not essential Understanding
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include a combination of advanced unsteady computational fluid dynamics (CFD) and also the assessment of the design via real-time piloted simulations. The post is full time and is fixed term until 31
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include a combination of advanced unsteady computational fluid dynamics (CFD) and also the assessment of the design via real-time piloted simulations. The post is full time and is fixed term until 31
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in aerothermal experiments and/or turbine design is essential. Experience in data analysis, design using FEA and CAD packages, as well as CFD is also desirable. Good time management, organisation and
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. The successful applicant will engage in computational analyses, and experimental validation including CFD and FEA, to understand and predict the flow behaviour and interface bonding during injection over-moulding
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to assist multiscale modelling for zero-excess solid-state batteries. The candidate is expected to be experience in mesoscale modelling (finite element, CFD, phase-field theory) for addressing scientific
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computational analyses, and experimental validation including CFD and FEA, to understand and predict the flow behaviour and interface bonding during injection over-moulding. They will work closely with leading
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goal. The Research Fellow will work under the supervision of the Surrey PI, Professor Jennifer Wen, to deliver Surry’s contribution to the project. The researcher will conduct CFD simulations to validate