Reduced-order modelling of the combustion dynamics of a rotating detonation engine
The development of more efficient propulsion technologies is of particular interest to transportation, space exploration, and defense. The rotating detonation engine (RDE) is a fairly new approach to high-speed propulsion that relies on detonation waves propagating continuously and circumferentially in an annular combustion chamber. The phenomena involved are multiphysical and multiscale in nature, making a fundamental understanding difficult and, consequently, presenting significant practical design challenges.
Research objectives
We are seeking a highly motivated student to begin working on this project in Fall 2025. This project aims to use reduced-order modelling and data-driven analysis techniques to reveal the multiscale combustion dynamics of a rotating detonation engine and to develop a predictive model. The model will be compared against numerical simulations using an existing solver such as OpenFOAM (computational fluid dynamics). The project will by co-supervised by professor Hoi Dick Ng from Concordia University.
Why join us?
This position comes with a competitive financial package and presents a unique opportunity to work on a cutting-edge topic with a big potential. You will join a dynamic and passionate team at the Laboratory for Fluid Mechanics and Applications (LFMA), where together we push the boundaries of fluid mechanics knowledge, analysis, and innovation. We use state-of-the-art experimental and numerical methods to explore complex and unsteady flows, from fundamental studies to real-world applications in aerospace, medicine, ventilation, and more. The LFMA possesses a recognized expertise in advanced post-processing and modelling methods applicable to a wide range of fluid flows.
How to apply?
Please provide a cover letter, a CV, and a recent transcript by email to Prof. Di Labbio. In your cover letter, you are invited to indicate any particular circumstances that may have impacted your professional career. Shortlisted candidates will be contacted for interviews.
Required knowledge
The student is expected to a have a good understanding of fluid mechanics and numerical methods, and good programming skills (e.g., MATLAB, Python).