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Position: PhD Position - Modelling of phase change in dense particle assemblies
Institution: University of Edinburgh
Location: Edinburgh, Scotland, United Kingdom
Duties: This project aims to deliver a new modeling approach to efficiently simulate the powder flow and phase change (solid-liquid-solid) in dense packings of powder consisting of tens of millions of individual grains with application to manufacturing processes. To achieve this the student will contribute to all aspects of the development (theoretical, implementation and validation) of a state-of-the-art, high-fidelity computational framework based on Discrete Element Method and lattice-Boltzmann modeling approaches and will perform computer simulation to assess the powder flow and phase change in dense packings. Through these numerical simulations, the student is expected to provide new insight into the effects of the grain shape on the powder dynamics and phase change in dense particle assemblies
Requirements: At least a 2: 1 Undergraduate degree in mechanical/chemical engineering, physics, applied math or closely related subject areas (MSc/MEng preferred). Strong math and computer skills (e.g. advanced mathematical modelling, computational PDEs, some exposure to HPC systems, understanding Linux CLI). Some experience in at least one high level programming language with a willingness to become proficient quickly (preferably Fortran or C++; Python and/or MATLAB also acceptable)
   
Text: Skip to main content HomeAboutStudyResearchAlumniBusinessContact Us School of Engineering > Schools & Departments Search form Search SCHOOL OF ENGINEERING You are hereHome » Study » Postgraduate Research » Study for a PhD » PhD Opportunites » Modelling of phase change in dense particle assemblies Modelling of phase change in dense particle assemblies This project aims to deliver a new modeling approach to efficiently simulate the powder flow and phase change (solid-liquid-solid) in dense packings of powder consisting of tens of millions of individual grains with application to manufacturing processes. To achieve this the student will contribute to all aspects of the development (theoretical, implementation and validation) of a state-of-the-art, high-fidelity computational framework based on Discrete Element Method and lattice-Boltzmann modeling approaches and will perform computer simulation to assess the powder flow and phase change in dense packings. Through these numerical simulations, the student is expected to provide new insight into the effects of the grain shape on the powder dynamics and phase change in dense particle assemblies. Further Information: At least a 2:1 Undergraduate degree in mechanical/chemical engineering, physics, applied math or closely related subject areas (MSc/MEng preferred). Strong math and computer skills (e.g. advanced mathematical modelling, computational PDEs, some exposure to HPC systems, understanding Linux CLI). Some experience in at least one high level programming language with a willingness to become proficient quickly (preferably Fortran or C++ - Python and/or MATLAB also acceptable). Please see details here: https://www.ed.ac.uk/equality-diversity Closing Date: Tuesday, November 30, 2021 Click here to Apply Now Principal Supervisor: Dr Sina Haeri Assistant Supervisor: Prof Yonghao Zhang Eligibility: Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants. Funding: Fully funded for home students / partially funded for International students. Further information and other funding options. UndergraduatePostgraduate TaughtPostgraduate ResearchStudy for a PhDPhD OpportunitesPhD ScholarshipsCDTsOur ResearchMSc by Research, MPhil and Visiting ResearchersPGR Additional InformationInternational StudentsWhy Edinburgh?Fees and FundingVisit UsApplySupport ServicesCareersStudent CommunityGo Abroad THE UNIVERSITY OF EDINBURGH Terms & Conditions Privacy Notice Privacy & Cookies Website Accessibility Freedom of information publication scheme Website Issue Reporting MyEd login Students Staff/PGR Alumni Social Media Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh.
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