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decision is made Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux
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Application Deadline: Applications accepted all year round How to apply: https://uom.link/pgr-apply-2526 UK Only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful
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Number AE2025-0514 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0514.pdf CALL FOR GRANT
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to carry out high-performance numerical simulations using our in-house CFD code, extract physical insights from simplified flow models, and characterise synchronisation thresholds and the robustness
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian You will be part of a dynamic research team working on topics relevant
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parameters, optimising these and various process conditions to enhance the overall performance of the gas turbine employing specific indicators. Used with a complementary CFD modelling approach, the research
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of gas emissions. This will involve leveraging advanced gas transport models, including advection-diffusion equations, computational fluid dynamics (CFD), and Navier-Stokes equations, to provide deeper
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CFD technologies. As the PhD researcher on this project, you will investigate and develop the numerical and algorithmic components needed to make this hybrid high order to low order strategy practical
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proposes to leverage CFD and DEM to develop an optimised methodology for designing and locating PBs specifically for enhanced flood mitigation in coastal environments. In particular, we will consider
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of numerical models (CFD) for the analysis and understanding of the behavior of the solution to be developed. Objectives:1. Designing a base design for incorporating a modular battery, 2. Develop and calibrate a