About the project
This project seeks to develop novel fluidic topology optimisation approaches for gas turbine component design by leveraging cutting edge machine and deep learning methods alongside computational fluid dynamics, ultimately aiming to revolutionise the solution of aerodynamic design problems.
Topology optimisation has grown in popularity over the past decade for structural problems but has yet to gain significant traction within the engineering community for aerodynamic problems. Although controlling the porosity over a control volume offers considerable design freedom, this approach tends to result in only a local optimum and struggles to effectively incorporate various constraints and objectives, such as manufacturability. This severely limits its application in gas turbine design.
This project aims to develop a novel approach to fluidic topology optimisation by building upon the cutting edge machine/deep learning approaches for optimisation and geometry generation developed by the Rolls-Royce University Technology Centre (UTC) for Computational Engineering.
By developing a unique feature-based fluidic topology optimisation process we aim to revolutionise aerodynamic design optimisation, producing more efficient designs in a greatly accelerated timeframe. While focused on gas turbine applications, for example, the optimisation of combustor, blade or seal features, this research has the potential to have a far reaching impact across engineering.
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent in one of the following:
- engineering
- mathematics
- computer science
Essential skills:
- experience of computer aided design such as Solidworks, NX or Catia
- experience of computational fluid dynamics such as Fluent, Star or OpenFOAM
- experience of programming such as Matlab, python or C/C++
Desirable skills:
- experience of gas turbine design
- experience of machine/deep learning tools such as pytorch or tensorflow
Fees and funding
We offer a range of funding opportunities for both UK and international students, including Bursaries and Scholarships.
To learn about funding opportunities visit our Doctoral College scholarships and bursaries information.
A number of studentships are available and funding is awarded on a rolling basis. Apply early for the best opportunity to be considered.
How to apply
You need to:
- choose programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- choose the relevant PhD in Engineering
- add name of the supervisor in section 2
Applications should include:
- personal statement
- your CV (resumé)
- 2 academic references
- degree transcripts to date
Contact us
Faculty of Engineering and Physical Sciences
If you have a general question, email our doctoral college (feps-pgr-apply@soton.ac.uk).
Project leader
For an initial conversation, email Dr David Toal (D.J.J.Toal@soton.ac.uk).
