Coupled fluid-structure simulations of industry relevant gas turbine technologies

Primary Supervisor: Professor Adrian Jackson

Project Overview

The aim of this PhD is to enable coupled simulations of fluid and structure as applied to realistic, industry relevant gas turbine technologies. Currently challenges for such simulations include scalability of the coupling solution (how many instances can/should be coupled), load balancing of the simulation, enabling changes in geometries, correctness of the data passed between codes, automated approaches for identifying convergence and divergence of running simulations, as well as support for tools (profiling and debugging).

Overview of the research area

The VECTA EPSRC Strategic Prosperity Partnership continues the work began in the ASiMoV project to develop the modelling capabilities to virtually design and certify the next generation of aeroengines. A significant challenge faced by these designs will be addressing their contribution to climate change. This will require engines that are more efficient than ever before, combined with alternative low-carbon and carbon-neutral fuels. Such fundamental changes will require unprecedented simulation capabilities to achieve high-resolution predictive capabilities for a new regime where decades of institutional knowledge cannot be relied upon. To do so, the entire simulation workflow, including the combustion modelling that is the focus of this project, will need to be Exascale-capable. For this project to succeed, the computational capability must be demonstrated in industry relevant geometries. The student will investigate and assess how to couple fluid-structure simulations of industry relevant geometries at Exascale, while maintaining scalability, correctness, security and accuracy.

Potential research questions

• What challenges do industry relevant geometries present?
  • How do we achieve scalability and performance whilst preserving security, e.g. through encryption?
  • How can data correctness be guaranteed?
• How can tools better support coupled simulations?
  • What information do we need from profilers and debuggers to asses performance and correctness?
• How is load balancing impacted by moving to realistic geometries?
  • How can we dynamically allocate resources to the fluid and structure simulations to minimise idle resources?
• How can we efficiently support heterogenous computing architectures to enable targeting parts of the coupled simulation at the most efficient hardware
  • As we are moving on to Exascale systems that heavily use GPU, which parts of the simulations will be most efficient on GPU, which on CPUs, and how do we manage the communications between them effectively?

Student Requirements

A UK Masters degree, 1^st in undergraduate integrated Masters, or its international equivalent, in a relevant subject such as computer science and informatics, physics, mathematics, engineering. 

The student must be a strong programmer in at least one of C, C++ or Fortran with experience of developing or contributing to scientific applications. The student must be familiar with mathematical concepts such as algebra, linear algebra, probability and statistics.

English Language requirements as set by University of Edinburgh

Important: Please note that there are restrictions on nationalities for the PhD studentship. If you are a national (or dual-national) of one of the countries on the US Commerce Control List (https://www.bis.gov/regulations/ear/746) you are not eligible to apply for this funding.

Recommended/Desirable Skills

Experience with numerical methods, scientific programming and HPC are highly desirable, as are an understanding of the fundamentals of CFD, combustion and/or numerical analysis. 

How to apply

Applications should be made via the University application form, available via the degree finder. Please note the proposed supervisor and project title from this page and include this in your application. You may also find this page is an useful starting point for a research proposal and we would strongly recommend discussing this further with the potential supervisor.

Further Information

• P.Bartholomew, A.Borissov, C.Goddard, S.Lakshminarasimha, S.Lemaire, J.Zarins & M.Weiland, “ASiMoV-CCS – A new solver for scalable and extensible CFD & combustion simulations”, PASC25 (2025), https://dl.acm.org/doi/10.1145/3732775.3733577
• Sam Curtis – PhD thesis (2025). “Coupled Multi-Physics Simulations: Using Mini-Apps to Explore Optimisation and Emerging Hardware for Large-Scale Problems”. https://wrap.warwick.ac.uk/id/eprint/191715