Airfoil and blade self-noise

翼型和叶片自噪声

• 批准号: RGPIN-2019-05844
• 负责人: Moreau, Stephane
• 金额: $ 5.13万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738541
• 关键词: Airfoil; blade; self; noise

The present research proposal focuses on airfoil and blade noise at low (subsonic) and high (transonic) speeds. These canonical problems are the building blocks for the noise prediction of any transport system including autonomous vehicles or drones. For instance it will directly contributes to the prediction and control of low and high speed fan noise involved in most ventilation and propulsion systems, as well as airframe noise generated by high lift devices or empennages. The proposal should then respond to important present and future environmental and health issues related to increasing air traffic, proliferation of autonomous vehicles and noisy work conditions. It should be complementary to the industrial Chair in Aeroacoustics at Université de Sherbrooke and the Collaborative Research projects which rather focus on the prediction and control of the full noise sources in the actual turbo-engine and ventilation systems, and on airframe noise. It should then strengthen the transportation industry that is one of the key economic sectors of Canada and help the Department of National Defense to detect and counter autonomous vehicles. It will also yield a reduction of greenhouse gas emissions by helping the certification and acceptation of electrical cars for which heating issues increase the cooling demands and consequently the ventilation needs. This research proposal is directed towards developing (1) numerical and analytical tools to simulate and predict aeroacoustic phenomena generated by the interaction of a flow with a solid surface, from the sources of noise (i.e. the emission phase) to their reception by a human being (i.e. the propagation phase), and (2) innovative noise control concepts and technologies to reduce these nuisances. Ultimately these prediction tools and noise control techniques will be applied at the system level to reduce the noise from low and high speed fans, high lift devices and autonomous vehicles. They will be integrated in their design process to guarantee that noise specifications of these products and new environmental regulations are met. Airfoil noise sources yield both tonal and broadband contributions that can be predicted by detailed compressible unsteady numerical simulations in the near-field accurately and propagated to the far field by an acoustical analogy. The resulting results are compared with measurements performed in open-jet anechoic wind tunnels to validate the improved acoustic analytical models.

目前的研究提案重点关注低（亚音速）和高（跨音速）速度下的机翼和叶片噪声，这些典型问题是包括自动驾驶车辆或无人机在内的任何运输系统噪声预测的基础。预测和控制大多数通风和推进系统中涉及的低速和高速风扇噪声，以及高升力装置或尾翼产生的机身噪声，该提案应应对当前和未来与增加空气有关的重要环境和健康问题。它应该是对舍布鲁克大学空气声学工业教授和合作研究项目的补充，这些项目侧重于预测和控制实际涡轮发动机和发动机中的全部噪声源。它将加强加拿大关键经济部门之一的交通运输业，并帮助国防部检测和应对自动驾驶汽车，从而减少温室气体排放。帮助认证和接受电动汽车的加热问题增加了冷却需求，从而增加了通风需求。本研究提案旨在开发（1）数值和分析工具来模拟和预测由流动与固体表面相互作用产生的气动声学现象，从噪声源（即发射阶段）到人类接收（即传播阶段），以及（2）减少这些滋扰的创新噪声控制概念和技术最终将是这些预测工具和噪声控制技术。应用在系统层面，以降低低速和高速风扇、高升力设备和自动驾驶车辆的噪音，它们将被集成到设计过程中，以确保满足这些产品的噪音规格和新的环境法规。音调和宽带贡献可以通过近场中的详细可压缩非定常数值模拟准确预测，并通过声学类比传播到远场。将所得结果与在开放喷射消声风洞中进行的测量进行比较，以验证改进的结果。声学的分析模型。