Applications are invited for a Research Associate/Fellow position available to work as part of a team which aims to develop novel numerical methods for fundamental investigations of flow boiling in microchannels.
The post is funded through the Engineering and Physical Sciences Research Council (EPSRC), under the grant “BOiliNg flows in Small and microchannels (BONSAI)”, and is part of a collaborative project involving the University of Nottingham, Brunel University London, Imperial College London, and 14 industrial and academic partners. The overall project aims at investigating the fundamental heat and mass transfer features of boiling flows in miniaturized channels. It combines cutting-edge experiments based on space/time-resolved diagnostics, with high-fidelity interface-resolving numerical simulations, to ultimately provide validated thermal-design tools for high-performance compact evaporators.
The successful candidate will develop physical and numerical models for the direct numerical simulation of boiling flows in small and microchannels using the open source package OpenFOAM and the built-in Volume-Of-Fluid method. The focus is on bubble nucleation, growth and subsequent flow patterns development within square and rectangular channels, modeling fluids and conditions emulating the experimental conditions studied by the project partners. The candidate will implement algorithms to improve the interface advection step, surface tension and phase-change estimation within the solver, focusing in particular on the development of a sub-grid evaporation microlayer model to capture heat transfer near contact lines. Other possible directions of the research are on the implementation of a phase field method in OpenFOAM to capture phases advection and related heat, mass and momentum exchanges at the liquid-vapour interface. The candidate will liaise with world-leading experimentalists at Brunel (Prof. Karayiannis) and Imperial College (Prof. Markides) to validate the numerical data and complement the boiling experiments and will develop prediction methods for boiling heat transfer assisted by machine learning algorithms in collaboration with the Alan Turing Institute and Imperial College (Prof. Matar).
Candidates must have or be near completion of a and PhD (essential) in engineering, applied mathematics or a related subject area, with a major component in using Computational Fluid Dynamics. You are also expected to have experience (essential) in OpenFOAM or equivalent opensource simulation tool and C++ programming, a strong foundation in multiphase flows, fluid mechanics and phase change processes, knowledge (essential) and experience (desirable) with related numerical methods. The ability to work in a team, and interact professionally with collaborators is essential as this project will operate in close collaboration with colleagues at other institutions.
This full-time (36.25 hour) post is available immediately and will be offered on a fixed-term contract for a period of 12 months. Job share arrangements may be considered.
To apply, please submit a CV, a publication list and a cover letter.
Informal inquiries may be addressed to Dr. Mirco Magnini, email firstname.lastname@example.org Please note that applications sent directly to this email address will not be accepted.