Flow-Induced Noise in Low- and High-Speed Flows: Towards the Development of a Quieter Environmentally Friendly Aircraft

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Noise is a type of environmental pollution. The World Health Organization defines environmental noise as a public health problem. Noise can cause hearing impairment, stress, cognitive impairment in children, and sleep disturbance. Aircraft noise has been linked to hypertension and heart disease, and impacts communities living in the vicinity of airports as well as people traveling aboard the aircraft. More recently, the International Civil Aviation Organization has adopted more stringent noise standards. Quieter aircraft technologies and accurate noise predictions are crucial to allow for these stricter regulations. My research career has been dedicated to understanding the nature of the turbulent boundary layer (TBL) and its interaction with structures as a source of noise. In aerospace, the TBL acting along the aircraft fuselage can result in unacceptable cabin noise levels and decrease the longevity of fuselage panels due to structural fatigue. Furthermore, the TBL interaction with aircraft surfaces is also an important source of external airframe noise, which impacts communities nearby airports. Mathematical models are often used to predict TBL behaviour, as well as noise produced by structures in contact with the TBL. The accuracy of these models is imperative for a reliable prediction of noise. However, current TBL models provide dissimilar predictions which are too large to support accurate predictions of panel response and related noise radiation. In this research program, I will create versatile TBL models for the accurate prediction of flow-induced noise in aircraft and the development of quieter designs. The proposed research will be mainly based on experimentation through low- and high-speed wind tunnel testing, followed by mathematical modelling for TBL models development, as well as computational methods. The simultaneous measurements of TBL wall-pressure fluctuations, particles' velocity near the wall, and sound pressure level, will enable the development of a more accurate TBL model prediction framework, decreasing the current uncertainty of predictions.  Our work will bring multiple benefits to Canada, including: the creation of innovative, accurate models for the prediction of TBL noise; a better understanding of the underlying factors that contribute to the inaccuracies in existing TBL models; and, the creation of a database of quieter aircraft designs. These contributions will translate into economic benefit and higher competitiveness of Canadian aerospace industry. Our work will also result in social benefits by contributing to the well-being and health of our communities, as well as in environmental benefits by promoting the development of quieter solutions. Finally, students in my research group will graduate with exposure to a unique combination of experimental and computational skills, which will be beneficial for careers in academia and industrial sectors, such as aerospace, automotive and mechanical engineering.