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

噪声是环境污染的一种。世界卫生组织将环境噪声定义为公共健康问题。噪音会导致听力障碍、压力、儿童认知障碍和睡眠障碍。飞机噪音与高血压和心脏病有关，并影响机场附近的社区以及乘坐飞机旅行的人。最近，国际民用航空组织采取了更严格的噪音标准。更安静的飞机技术和准确的噪音预测对于这些更严格的监管至关重要。我的研究生涯一直致力于了解湍流边界层(TBL)的性质及其与作为噪声源的结构的相互作用。在航空航天中，沿飞机机身作用的TBL会导致不可接受的座舱噪声水平，并由于结构疲劳而降低机身壁板的寿命。此外，TBL与飞机表面的相互作用也是机身外部噪声的重要来源，影响了机场附近的社区。数学模型经常被用来预测TBL的行为，以及与TBL接触的结构产生的噪声。为了可靠地预测噪声，这些模型的准确性是必不可少的。然而，当前的TBL模型提供的不同预测太大，不能支持对面板响应和相关噪声辐射的准确预测。在这个研究计划中，我将创建通用的TBL模型，用于准确预测飞机内的流动诱导噪声，并开发更安静的设计。建议的研究将主要基于低速和高速风洞试验的实验基础上，其次是建立TBL模型的数学模型，以及计算方法。对TBL壁压波动、壁面附近粒子速度和声压级的同时测量，将有助于开发更准确的TBL模型预测框架，减少当前预测的不确定性。我们的工作将为加拿大带来多重好处，包括：创建用于预测TBL噪声的创新、准确的模型；更好地了解导致现有TBL模型不准确的潜在因素；以及创建更安静的飞机设计数据库。这些贡献将转化为加拿大航空航天产业的经济效益和更高的竞争力。我们的工作还将通过促进我们社区的福祉和健康而产生社会效益，并通过促进开发更安静的解决方案来产生环境效益。最后，我的研究组的学生毕业时将接触到实验和计算技能的独特组合，这将有利于在学术界和工业部门的职业生涯，如航空航天、汽车和机械工程。

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.