Context

City, University London (CITY), established in 1894, is a global University, part of the University of London, committed to academic excellence with a focus on business and the professions and an enviable central London location. The University is in the top 5% of universities in the world and attracts over 21,000 students from around 160 countries. The School of Science Technology has been leading education and research in engineering and mathematics for more than a hundred years. The Department of Mechanical Engineering is the home for the ThermoFluids Research Centre (TFRC) and the Aeronautics and Aerospace Research Centre, the low-turbulence tunnel of which is part of the UK’s National Wind Tunnel Facility. TFRC maintains strong links with automotive, fuels and fuel additives industries that actively build our international reputation. Since 2013, TFRC has coordinated more than 15 EU-funded research grants. The 2014 Research Excellence Framework (REF) showed a significant improvement in our research standing, with 79% of its staff rated as world-leading and internationally excellent.

Job Purpose

City, University of London along with Otto von Guericke University Magdeburg (DE), Lund University (SE), National Technical University of Athens (GR) and industrial partners Lubrizol Ltd (UK) and AVL List Gmbh (AT) (from now on referred to as ‘The Team’,) have been successful in their project proposal E-COOL, ‘A Holistic Approach for Electric Motor Cooling’, submitted to the European Innovation Council (EIC). The Team is looking to appoint one Postdoctoral Research Associate.

E-COOL aspires to develop a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. The project aims to achieve this technological breakthrough at time-scales compatible to those required for industrial innovation, in a bespoke manner integrating two interdisciplinary activities: (a) development and synthesis of novel oil-based, dilute polymer mixtures of non-Newtonian nature, which, when employed in spray-cooling systems, have the potential to be a disruptive technology; (b) implementation of a universal design methodology for such systems optimised with the aid of new Machine Learning (ML) algorithms. Training datasets for the ML tool will be provided by accurate ‘ground-truth’ experimental and numerical investigations also to be conducted for the first time in E-COOL. The envisioned cooling system aims to provide unprecedented cooling rates at local temperature hot spots, contributing to an average 20% increase in e-motor efficiency compared to today’s state-of-the-art. This will allow next-generation e-motor utilisation over the whole range of transportation sectors, thus, facilitating significant additional energy and CO2 savings.

Main Responsibilities

Successful candidates are expected to contribute to the following main duties:

• To undertake research in the field specified to meet the aims, objectives and project specifications given in the proposal funded to create this appointment.

• To liaise closely with the academic and industrial partners of the project.

• To play a leading role in raising the national and international profile of The Team by publishing articles in international journals, attending conferences, enhancing appropriate links with industry and Institutions and through other appropriate routes.

• To prepare and make presentations of the work to City, University of London (CUL) and at major meetings and Conferences, as specified by the Principal Investigators and/or Head of Centre/or the Dean.

• To work as a member of the research centre within the discipline, playing a full part in the research life of the research team of the partner institutions.

• To play an appropriate role in planning and shaping future strategy and direction, working with other staff within The Team in a collegiate framework.

• To undertake other duties as required by the project coordinator.

Research

• To build upon the previous experience of the Team on the Computational Fluid Dynamics (CFD) simulation of non-Newtonian/viscoelastic fluids and to develop novel closures for fluid rheology using Tensor-Basis-Neural-Network (TBNN) architectures.

• To work with The Team, in order to develop reliable numerical methodologies capable of simulating the flow and thermal behaviour of complex heat-transfer liquids suitable for thermal management systems of electric motors.

• To collaborate with existing members of The Team, bringing together areas of expertise for innovative analytical and numerical research.

• To take an appropriate role in facilitating inter-disciplinary research links with other research centres and groups.