£5M EPSRC Programme Grant awarded

£5M EPSRC Programme Grant awarded to develop ground-breaking modelling capability in multiphase flows

A new EPSRC Programme Grant has been awarded to harness the synergy between world-leading scientists from four prestigious institutions to carry out the next generation of research into Multi-scale Examination of MultiPHase physIcs in flowS (MEMPHIS). This project is part of major £13.6 million boost for cutting-edge engineering research (www.epsrc.ac.uk/newsevents/news/2012/Pages/engineeringresearch.aspx).

The team comprises leading academics in multiphase flow research at Imperial College (Professor Omar Matar, Professor Chris Pain, Professor Geoffrey Hewitt), Birmingham (Professor Mark Simmons), Nottingham (Professor Barry Azzopardi) and University College London (Dr Panagiota Angeli) who will work together to create the next generation of modelling tools for complex multiphase flows.

Representing the team, Professor Omar K. Matar (Director) and Professor Mark Simmons (Deputy Director) state:

“The ability to predict the behaviour of multiphase flows reliably will address a major challenge of tremendous economic, scientific, and societal benefit to the UK. These flows are central to micro-fluidics, virtually every processing and manufacturing technology that exists, oil-and-gas and nuclear applications, and biomedical applications such as lithotripsy and laser-surgery cavitation. Current models employed both in academia and in practice rely on empirical methods, which are difficult to extrapolate and narrow in scope. Our new modelling framework represents a paradigm-shift in multiphase flow research worldwide.”

The research will achieve this goal by exploiting recent developments in parallel computation, being capable of running efficiently on supercomputers with up to one million processors using the most sophisticated multi-scale physical models. This framework will offer unprecedented resolution of multiphase flow phenomena. A transparent linkage between model inputs and prediction is a novel component of the unified model, achieved by using systematic approach to identify error-sources and directed model-driven experiments. This will maximise prediction accuracy in a way which has not been done before.

The capabilities of the new framework will be demonstrated in two areas of strategic importance to the UK: by providing insights into the manufacture of home and personal care products and catalysts, and reliable prediction of multiphase flow regime transitions in the oil-and-gas industries.

There will be at least nice new Ph.D. students and five Postdoctoral Research Associates working as part of the Programme. Anyone interested in Ph.D. or postdoc opportunities please contact Professor Mark Simmons (m.j.simmons@bham.ac.uk)