Structural and topological information play a key role in behaviour of flow and transport through very complex geometries.
Examples range from flows involving droplets dispersed in turbulent air, urban flows, medical applications like body cell absorption/extraction of fluids, flows past canopies in either textiles or when looking at tree configurations in forests, flows through rocks (relevant to oil and gas industry) to flows in media with dynamically changing configurations of like bubbles.
Scales involved can vary from microfluids to very large. Accurate simulations of such multiscale flows may be prohibitively expensive or take too long for practical application. To alleviate this, a model reduction strategy can be used which combines highly accurate information obtained at small scales and incorporates it to flows evolving at larger scales. The project will involve a development of a new reduced model approach, for a selected challenging computational fluid dynamics problem. The reduced model will build on a range of high-resolution simulations at small scales, and their application within the model.
This project offers an opportunity to use a novel immersed boundaries based numerical approach developed at Loughborough University to perform challenging direct simulations reflecting the fine-scale processes. There is also a possibility to employ Artificial Intelligence techniques to speed up computations further by identifying preferred directions of flow in the porous media networks – mimicking phenomena occurring in nature. Accurate simulations of fully multiscale flows especially through complex geometries are seldom attempted and the project is likely to provide the first-ever computations of its kind. The numerical approach will employ a massively parallel, high-resolution scheme, with available DNS, LES, ILES, and DES turbulence treatments. Noteworthy are particularly Implicit Large Eddy Simulation (ILES) providing a high degree of novelty in this context.
The Wolfson School provides a prestigious and inclusive environment for research, with a thriving doctoral community. Renowned for impactful research with global benefits, we rank 62nd worldwide in Mechanical, Aeronautical and Manufacturing Engineering (QS 2023).
PhD students at Wolfson receive generous additional funds to support individual development, including travel, attending conferences, and training programs.
The School of Mechanical, Electrical and Manufacturing Engineering has seen 100% of its research impact rated as 'world-leading' or 'internationally excellent' (REF, 2021).
Primary supervisor: Joanna Szmelter
Secondary supervisor: Minsuok Kim
Entry requirements for United Kingdom
Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in Engineering, Physics, Mathematics, Computer Science, or a related subject. Programming and model development experience and/or understanding of concepts of numerical methods, fluid dynamics, and CFD will be beneficial.
A relevant master’s degree and/or experience will be advantageous.
How to apply
All applications should be made online. Under programme name Mechanical and Manufacturing Engineering. Please quote the advertised reference number: SA24-JS in your application.
Competition for funded entry is high, so please ensure that you submit a CV and the minimum supporting documents. Failure to do so will mean that your application cannot be taken forward for consideration.
The following selection criteria will be used by academic schools to help them make a decision on your application.