Numerical modelling of multiphase flows

The project aims to develop numerical framework which can be applied to various multiphase flow problems (gas-liquid, gas-liquid-solid, etc.) in engineering and scientific research fields such as energy, environment and manufacturing. Although there are huge demands of practical multiphase flow simulations, there is no established numerical framework which can simulate a wide variety of practical multiphase flow problems.
The supervisor research team already has highly unique and world-leading numerical framework for multiphase flow simulations (see http://goo.gl/CYE1RA). The PhD student can work based on the existing numerical framework, and is expected to improve/modify the numerical framework and numerically study multiphase flow phenomena. The PhD student can select some of the following topics.

Possible research topics in numerical modelling:
1. Turbulence modelling in multiphase flows
2. Interactions between multiphase flows and structures
3. Phase changes
4. Contact angle modelling
5. Developments of hyperbolic equation solvers
6. High performance computing (massively parallel computing, GPU computing)
7. etc.

Possible research topics in fluid phenomena:
1. Energy: primary atomization, energy mining, cooling system (boiling), etc.
2. Environment: CO2 capturing, rain drop formations, heat transfer across ocean surfaces, Tsunami/flood damage predictions, etc.
3. Manufacturing: inkjet, coating, spray cooling, etc.

There are many other possible topics.

The applicants should have a strong background in mathematics (undergraduate 1st and 2nd year engineering mathematics level) and computer programming. Candidates from physics, mathematics, computer science as well as engineering are welcome.

Some high-end numerical algorithms and software will be developed. These algorithms and software can be used for a wide variety of research fields as indicated above. There are opportunities for collaboration with Tokyo Institute of Technology, JAMSTEC and Beijing Computational Science Research Centre, etc.

Candidates should hold or expect to gain a first class degree or a good 2.1 and/or an appropriate Master’s level qualification (or their equivalent).

Applicants whose first language is not English will be required to demonstrate proficiency in the English language (IELTS 6.5 or equivalent)