Effect of Separation and Stall on Aerofoil Noise

ce51e2e3-8550-4926-aba2-0c78dfe0e149

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EPSRC
EPSRC
EPSRC
EPSRC
EPSRC

£2,172,045

May 31, 2018

June 30, 2022

It is well established that long-term exposure to aircraft and wind turbine noise is responsible for many physiological and psychological effects. The World Health Organization estimated in 2011 that up to 1.6 million healthy life years are lost annually in the western European countries because of exposure to high levels of noise. This is in direct conflict with the further increase in the number of flights in the EU and US and development and further expansion of on-shore wind farms. Therefore, it is critical to better understand the noise generation mechanism from different aero-components and develop tailored noise reduction methods in order to reduce the noise at source. Amongst all components, understanding of noise generation from aerofoils is of great importance, due to its contribution to the overall noise of aircraft or wind turbine. To a great extent, our current knowledge of aerofoil noise generation is limited to aerofoils at low angles of attack. However, most aerofoils are operated at higher angles of attack to maximise aerodynamic performance where they are prone to separation and stall, especially when they are operating under varied conditions. In these situations, the noise generation as well as the flow mechanisms are substantially different compared to lower angles of attack. Our knowledge and understanding of the mechanisms as well as our ability to predict these noise sources is limited.

This collaborative project, which includes contributions from industrial partners, aims to develop new understanding of noise generation mechanisms in the presence of separation and stall. The goal is to perform experiments and numerical simulations in order to establish a high-fidelity database of flow and noise for over a wide range of operating conditions. The data will then be used to identify flow mechanisms that contribute to the different aerofoil noise sources at high angles of attack. The experimental and numerical data will also be utilised to develop new fully-validated models for noise prediction, which can then be used by our industrial partners (GE-Dowty and Embraer) to improve the design of next generation of lifting surfaces across different applications. Overall, this project will bring about a step change in our understanding of noise generation mechanisms across the entire regime and pave the way to more accurate noise predictions and development of potential noise mitigation strategies.

Potential Impact:
Impact on People and Society - Exposure to high levels of noise over long periods of time can cause serious physiological to psychological problems, such as hearing impairment, communication interference, sleeplessness, annoyance, task interference, learning difficulties, etc. This is particularly the case for the residential areas near large airports and wind farms. The significant increase in the number of short- and mid-range flights in the near future and also construction of new large wind-farms will mean that more people will be exposed to high levels of noise. A major part of this noise is due to the flow interaction with aerofoils. This project is to tackle the aerofoil noise problem at a fundamental level, enhancing our understanding of the noise generation mechanism and ultimately helping the development of more robust noise reduction methods.

Impact on Economy and Industry - The proposed work is of high relevance to aviation and wind energy Industries. To meet their environmental targets, the aviation and wind energy sectors need to gradually improve their products and reduce their noise signature. Therefore, the ability to understand the noise generation, particularly aerofoils, and accurately predict the noise level is of great importance. The proper understanding of the noise generation can also help the industry to come up with tailored passive or active noise control methods. Part of this project is funded by Industry to ensure a proper knowledge transfer during the course the research and development of an industrially viable noise prediction method based on the findings of this research.