Project description:

Porous materials, consisting of solid structures permeated by a network of 
interconnected pores, have been a focal point in both academic research and 
industrial applications for flow and thermal control for over five decades. 
These applications encompass a wide range of uses, including transpiration 
cooling, packed bed energy storage, cooling systems for batteries and LEDs, and 
even noise mitigation for aerospace and wind turbine applications. In these 
contexts, a deep and fundamental comprehension of the interaction between fluid 
flow and porous media at the pore-scale is pivotal for achieving efficient flow 
and thermal control using these materials.

In this research project, we will explore the utilisation of smart porous 
materials for enhancing flow and thermal control in aerospace and renewable 
energy systems. Our investigation will encompass a fundamental analysis of fluid 
flow and heat transfer within these porous materials, with the overarching goal 
of gaining profound insights into pore-scale flow characteristics. Our 
methodology involves employing Large Eddy Simulation approach, coupled with 
Machine Learning methodologies. Through this integrated approach, we will 
conduct a comprehensive examination of high Reynolds number turbulent flows and 
temperature distributions within porous media systems. 

Team Members:
The project involves collaboration with the University of Bristol for 
experiments and the University of Southampton for DNS research. The PhD student 
will have the chance to visit these institutions for data collection. They will 
join a dynamic research team comprising five academics, three postdoctoral 
researchers, and seven PhD students focusing on various aspects of porous 
materials. The student will have close engagement with several industrial 
partners, including EDF-Energy and BL Refrigeration and Air Conditioning Ltd. 
Additionally, they will participate in biannual formal project review meetings 
held at these companies.

Key skills required for the post:
•	Computational skills related to computational fluid dynamics (CFD);
•	Excellent understanding of Fluid Dynamics and Heat Transfer sciences;
•	Experience in using Fluent, OpenFoam, and Machine Learning techniques is 
advantageous.

Entry requirements:
MEng, MSc degree or equivalent with a background in Mechanical, Applied 
Mathematics, Physics, Chemical Engineering, Aerospace Engineering , or a related 
discipline

Key transferable skills that will be developed during the PhD:
At the end of the project you will have acquired the expertise of CFD technique 
in fluid dynamics and heat transfer of turbulent flow in porous media. PhD 
students are supported to participate in international conferences in North 
America, Europe and Asia, such as International Conference on heat Transfer and 
the UK Heat Transfer Conference. These events will provide a platform to develop 
a network of professional contacts for further career progression.

How to apply:
You will need to submit an online application through our website here: 
https://uom.link/pgr-apply. When you apply, you will be asked to upload the 
following supporting documents: 
•	Transcript and certificates of university level qualifications
•	CV
•	Contact details for two referees 
•	English Language certificate (if applicable. Home students will not need 
to provide this)

We recommend that you contact the supervisor to discuss the application before 
you apply. The contact supervisor for this project is Dr Yasser Mahmoudi 
(yasser.mahmoudi@manchester.ac.uk)


Funding Notes:
•	The PhD is 3.5 years long and can start in 2024.
•	The School of Engineering at the University of Manchester will fund the 
PhD; this will include home fees and the UKRI stipend each year. The UKRI 
stipend for the year 2023/2024 is £18,622 (tax free). PhD students in the School 
can apply to be Teaching Assistant, potentially earning over £2,500 annually.