Optimising Surface Topography for Drag Reduction in Turbulent Flows

This PhD project focuses on advancing passive control strategies to reduce drag in turbulent flows by developing optimised surface topographies. Recent experimental breakthroughs have shown that drag reduction is possible even at high Reynolds numbers by targeting large-scale turbulent structures, challenging the limits of traditional approaches. Inspired by this, the project explores the design of stationary, non-planar surfaces that induce beneficial flow structures close to the wall, aiming to reduce drag without energy input. Such surfaces are envisioned to target a wider range of turbulent scales, providing efficient and sustainable solutions for friction reduction in engineering applications.

The project’s key objectives include:

1. building a computational framework to predict the flow over complex topographies and estimate drag reduction
2. systematically designing optimised surfaces that exploit turbulence dynamics for drag control. 

This will involve Reynolds-Averaged Navier-Stokes (RANS) simulations to capture the three-dimensional mean flow over non-planar surfaces, combined with linear input-output analysis to examine how different topographies influence turbulent flow structures across scales.

Using this approach, you will apply gradient-based and Bayesian optimisation methods to explore large design spaces, iteratively refining surface patterns to achieve maximum drag reduction. Beyond engineering applications, this work also aims to enhance the understanding of flow-topography interactions and the physics of turbulence manipulation.

This PhD opportunity is ideal for candidates with a strong background in fluid dynamics who wish to contribute to the future of energy-efficient design in fluid systems. Training will be offered for the use of the high-performance computing facilities at the University of Southampton.