College of Science & Engineering

Numerical Investigation of the Vortex Ring State for Rotary Wings

Supervisor: Dr Tao Zhang and Prof George Barakos

Industry Partner: GARTEUR Action Group 28 

School: Engineering

Description:

The Vortex Ring State (VRS) is a dangerous and complex aerodynamic phenomenon common in wind turbines, helicopters, and emerging future flight vehicles. It is a state where turbines and rotors are trapped in their own aerodynamic wakes, typically in adverse wind or descending maneuver. When the VRS happens, rotor or turbine blades often experience sudden load changes and loss of controllability. This had caused several severe accidents of the V22 tilt-rotor rotorcraft. For emerging sustainable energy and future flight systems, e.g. multi-rotor turbines/rotorcraft, the VRS is expected to be much more complicated, yet our understanding of this phenomenon is still very much limited.  

The proposed research hence aims to narrow our knowledge gap about this critical aerodynamic phenomenon and provide insight for safe design and operation of future rotary wing systems for green energy and aviation.  

Research objectives: 

The objectives are to: (1)explore suitable high-fidelity aerodynamic simulation strategies for the VRS; (2)identify and understand key aerodynamic patterns of the VRS and their impact on rotary wings; (3)engage with our EU partners in the GARTEUR AG-28 group. 

Methodologies, workplans, and outcomes: 

This study has two parts: aerodynamic modelling and flow analysis.  

For the modelling(weeks1-8), we will use the world-leading Helicopter Multi-Block3(HMB3) CFD framework developed at UofG. The study will first investigate various high-fidelity modelling strategies(weeks1-3). This allows training time for the student, and will derive a suitable modelling strategy balancing physical resolution and computational cost for the VRS(outcome1).  

The study will then systematically model the VRS flow physics(weeks3-8) looking into critical parameters e.g. rotor thrust and turbulence strength. This will establish a comprehensive high-fidelity VRS database(outcome2).   

The flow analysis(weeks5-10) will focus on identifying key flow patterns as modelling results gradually populate. This will adopt modal decomposition techniques to extract dominant VRS features(outcome3). We will then establish quantitative parameter correlations using these modes and data via Physics-informed Neural Network approaches(outcome4).  

Partners: 

This study works closely with the GARTEUR AG-28, a volunteering research group involving top institutions across Europe/UK. The group aims to share state-of-the-art experimental/numerical data to improve VRS understanding. The student will contribute to this research community and receive guidance from the group. Moreover, the student will benefit from the data generated by our EPSRC-funded GAAPS project now reaching its peak output. This combination of EU/UK expertise provides the ideal environment for a young student to experience research