课题基金 / 基金详情

Airfoil and blade self-noise

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:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
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项目摘要

项目成果

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中文摘要
翻译
目前的研究方案集中在低(亚音速)和高(跨音速)速度下的翼型和叶片噪声。这些典型问题是包括自动驾驶车辆或无人机在内的任何交通系统噪音预测的基石。例如,它将直接有助于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,以及由高升力装置或尾翼产生的机身噪声。然后,该提案应该对与空中交通增加、自动驾驶车辆激增和嘈杂工作条件有关的当前和未来重要的环境和健康问题做出回应。它应该是对舍布鲁克大学空气声学工业教席和合作研究项目的补充,这些项目更侧重于预测和控制实际涡轮发动机和通风系统中的全部噪声源,以及机身噪声。然后,它应该加强作为加拿大关键经济部门之一的运输业,并帮助国防部检测和打击自动驾驶车辆。它还将通过帮助认证和接受电动汽车来减少温室气体排放,因为供暖问题增加了冷却需求,从而增加了通风需求。这项研究建议旨在开发(1)数值和分析工具,以模拟和预测从噪声源(即发射阶段)到人类接收(即传播阶段)的流动与固体表面相互作用产生的空气声学现象,以及(2)减少这些滋扰的创新噪声控制概念和技术。最终,这些预测工具和噪声控制技术将应用于系统层面,以降低来自低速和高速风扇、高升程设备和自动驾驶车辆的噪声。它们将被整合到他们的设计过程中,以确保这些产品的噪音规范和新的环境法规得到满足。翼型噪声源产生音调和宽带贡献,可以通过详细的可压缩非定常数值模拟在近场准确预测,并通过声学类比传播到远场。将计算结果与开放式消声风洞的测量结果进行了比较,以验证改进的声学分析模型。
英文摘要
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.
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Measurement of detailed flow statistics for trailing-edge noise prediction and mitigation
  • 批准号:
    RTI-2022-00265
  • 项目类别:
    Research Tools and Instruments
  • 资助金额:
    $10.52万
  • 财政年份:
    2021
  • 负责人:
    Moreau, Stephane
  • 依托单位:
Airfoil and blade self-noise
  • 批准号:
    RGPIN-2019-05844
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $5.13万
  • 财政年份:
    2021
  • 负责人:
    Moreau, Stephane
  • 依托单位:
DETONATION : Prédiction et optimisation des sources acoustiques à l'aide de l'apprentissage profond
  • 批准号:
    568515-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $2.84万
  • 财政年份:
    2021
  • 负责人:
    Moreau, Stephane
  • 依托单位:
Quiet Electrical cooling Fan module (Qe-FAN)
  • 批准号:
    538116-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $4.69万
  • 财政年份:
    2021
  • 负责人:
    Moreau, Stephane
  • 依托单位:
海外基金