I am a researcher in the Thermofluids group at the School of Mechanical, Aerospace and Civil Engineering, UoS. My research focuses on computational modelling of turbulent flows and boiling heat transfer phenomena with particular applications for aerodynamics and power generation with nuclear reactors.
Interests
- Computational fluid dynamics
- Data assimilation
- Machine learning
- Engineering design optimisation
- Aerodynamics
- Nuclear thermal hydraulics
Education
PhD Aerospace Engineering
Univeristy of Sheffield
MEng Aerospace Engineering
University of Sheffield
Global Engineering Education Exchange programme
University of Michigan
Research
My research focuses on advancing computational modelling techniques for complex fluid dynamics, with a particular emphasis on turbulence and heat transfer phenomena. By combining traditional physics-based approaches with modern data-driven methods, including machine learning, I aim to improve the accuracy and efficiency of simulations in engineering applications. This work has broad implications, from optimising boiling heat transfer in nuclear reactors to enhancing the performance of aerospace propulsion systems. My goal is to bridge the gap between experimental data and computational models, enabling innovative solutions to challenging engineering problems.
Recent Publications
(2025).
Assessment of Heat Flux Partitioning Approaches for the Prediction of Subcooled Flow Boiling.
Proceedings of 21st International Topical Meeting on Nuclear Reactor Thermal Hydraulics.
(2024).
A Hybrid RANS-LES Dataset for Data-Driven Turbulent Mean Flow Reconstruction.
Springer Nature Switzerland.
(2024).
Sensor placement for data assimilation of turbulence models using eigenspace perturbations.
Physics of Fluids, AIP Publishing.
(2024).
A Priori Sensor Placement Strategy for Turbulent Mean Flow Reconstruction Using Parametric Model Perturbations.
American Institute of Aeronautics and Astronautics.
Featured Publications
Talks
