LU
Single-turbine scale quantification of wake turbulence
✓ Fully Funded
🎓 Aerospace Engineering
🎓 Applied Mathematics
🎓 Computational Physics
🎓 Engineering Mathematics
🎓 Environmental Physics
🎓 Fluid Mechanics
🎓 Mathematical Modelling
🎓 Mechanical Engineering
🎓 Meteorology
🎓 Stochastic Processes
offshore wind
DNS
LES modelling
Navier-Stokes simulation
aerodynamic interactions
environmental effects
flow control
turbulence physics
wake turbulence
wind turbine aerodynamics
This PhD quantifies single-turbine wake turbulence to improve understanding of flow physics, aerodynamic interactions, and impacts on downwind turbines, combining numerical simulation, data analysis, and model development.
Project Description
Turbulent wakes from individual wind turbines affect downstream turbine performance, increase fatigue loads, and influence environmental factors such as noise and large-scale atmospheric flow structures. This project focuses on:
Investigating non-local energy transfers in near-field wakes and their relation to pressure fields
Developing practical subgrid-scale models informed by high-fidelity simulations
Performing direct numerical simulations (DNS) of incompressible Navier-Stokes equations with turbine forcing
Analysing large datasets to extract and summarise physical mechanisms
Formulating large-eddy simulation (LES) parameterisations based on DNS outcomes
Optionally linking numerical results with field experiments conducted at the University of Minnesota
The work will produce models that better predict turbine wake behaviour and guide improved wind farm design and operation strategies.
Entry Requirements
First-class Honours degree, 2:1 plus Masters, or Masters with Distinction in Engineering, Mathematics, Physics, or related fields
English proficiency: IELTS 7.0 overall (min 6.0 in each skill)
Eligibility: Home students (UK residency rules apply)
Guaranteed interview scheme for eligible home students from underrepresented ethnic backgrounds
English proficiency: IELTS 7.0 overall (min 6.0 in each skill)
Eligibility: Home students (UK residency rules apply)
Guaranteed interview scheme for eligible home students from underrepresented ethnic backgrounds
How to Apply
Applications submitted to Loughborough University via the Offshore Wind CDT website. Rolling application for September 2026 entry; early submission encouraged.
Eligibility
UK/Home
EU
International
Supervisor Profile
PC
Prof Chris Keylock, Dr Yi Li, Prof Michele Guala
Loughborough University, Offshore Wind CDT
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