Aeroacoustics of Dynamic Stall
动态失速气动声学
基本信息
- 批准号:EP/X019284/1
- 负责人:
- 金额:$ 87.22万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
It is well established that long-term exposure to aircraft and wind turbine noise is responsible for many physiological and psychological effects. According to the recent studies, noise not only creates a nuisance by affecting amenity, quality of life, productivity, and learning, but it also increases the risk of hospital admissions and mortality due to strokes, coronary heart disease, and cardiovascular disease. 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. The noise is also acknowledged by governments as a limit to both airline fleet growth, acceptability of Urban Air Mobility, operation and expansion of wind turbines, with direct consequences to the UK economy.With regards to aerodynamic noise, aerofoil noise is perhaps one of the most important sources of noise in many applications. While aerofoils are designed to achieve maximum aerodynamic performance by operating at high angles of attack, they become inevitably more susceptible to flow separation and stall due to changing inflow conditions (gusts, wind shear, wake interaction). Separation and stall can lead to a drastic reduction in aerodynamic performance and significantly increased aerodynamic noise. In applications involving rotating blades, the near-stall operation of blades, when subjected to highly dynamic inflows, gives rise to an even more complex phenomenon, known as dynamic stall. While the very recent research into the aerodynamics of dynamic stall has shown the complexity of the problem, the understanding of dynamic stall noise generation has remained stagnant due to long-standing challenges in experimental, numerical and analytical methods. This collaborative project, which includes contributions from strong industrial and academic advisory boards, aims to develop new understanding of dynamic stall flow and noise and develop techniques to control dynamic stall noise. The team will make use of the state-of-the-art experimental rigs, dedicated to aeroacoustics of dynamic stall and GPU-accelerated high-fidelity CFD tools to generate unprecedented amount of flow and noise data for pitching aerofoils over a wide range of operating conditions (flow velocity, pitching frequency/amplitude, etc.). The data will then be used to identify flow mechanisms that contribute to the different aerofoil noise sources at high angles of attack, including aerofoil unsteady loading and flow quadrupole sources, and detailed categorisation of dynamic stall regimes. A set of new frequency- and time-domain analytical tools will also be developed for the prediction of dynamic stall noise at different dynamic stall regimes, informed by high-fidelity experimental and numerical datasets. This project will bring about a step change in our understanding of noise from pitching aerofoils over a wide range of operations and pave the way to more accurate noise predictions and development of potential noise mitigation strategies.
众所周知,长期接触飞机和风力涡轮机噪音会造成许多生理和心理影响。根据最近的研究,噪音不仅会影响舒适度、生活质量、生产力和学习,造成滋扰,还会增加因中风、冠心病和心血管疾病而入院和死亡的风险。世界卫生组织 2011 年估计,西欧国家每年因暴露于高强度噪音而损失多达 160 万健康生命年。政府也承认噪音限制了航空公司机队的增长、城市空中交通的可接受性、风力涡轮机的运行和扩展,对英国经济产生直接影响。就空气动力噪音而言,机翼噪音可能是影响英国经济的因素之一。许多应用中最重要的噪声源。虽然机翼的设计目的是通过在大攻角下运行来实现最大的空气动力性能,但由于流入条件的变化(阵风、风切变、尾流相互作用),它们不可避免地更容易受到流动分离和失速的影响。分离和失速会导致空气动力学性能急剧下降并显着增加空气动力学噪声。在涉及旋转叶片的应用中,叶片的近失速运行在受到高动态流入时会产生更为复杂的现象,称为动态失速。虽然最近对动态失速空气动力学的研究表明了问题的复杂性,但由于实验、数值和分析方法长期存在的挑战,对动态失速噪声产生的理解仍然停滞不前。该合作项目包括强大的工业和学术顾问委员会的贡献,旨在发展对动态失速流和噪声的新理解,并开发控制动态失速噪声的技术。该团队将利用最先进的实验装置,专用于动态失速气动声学和 GPU 加速的高保真 CFD 工具,以生成前所未有的大量流量和噪声数据,用于在广泛的操作范围内俯仰机翼条件(流速、俯仰频率/幅度等)。然后,这些数据将用于识别在高攻角下造成不同机翼噪声源的流动机制,包括机翼不稳定载荷和流动四极源,以及动态失速状态的详细分类。还将开发一套新的频域和时域分析工具,用于根据高保真实验和数值数据集预测不同动态失速状态下的动态失速噪声。该项目将彻底改变我们对各种操作中俯仰翼型噪声的理解,并为更准确的噪声预测和开发潜在的噪声缓解策略铺平道路。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mahdi Azarpeyvand其他文献
A Data-Driven Method for Stall Noise Predictions
失速噪声预测的数据驱动方法
- DOI:
10.2514/6.2024-3128 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Aurelien Ghiglino;Beckett Y. Zhou;John Branch;B. Zang;Mahdi Azarpeyvand;Jose Rendón;Stephane Moreau - 通讯作者:
Stephane Moreau
Experimental Characterisation of Cylinder-Induced Turbulence Ingestion in Propellers Operating in Edgewise Flight
边缘飞行中螺旋桨中气缸引起的湍流吸入的实验特征
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Liam Hanson;B. Zang;Mahdi Azarpeyvand - 通讯作者:
Mahdi Azarpeyvand
A Preliminary Noise and Flow Field Study of a Propeller Tilted Negatively to a Free-Stream
负倾斜自由流螺旋桨噪声和流场的初步研究
- DOI:
10.2514/6.2024-3385 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Liam Hanson;Desmond Lim;Xiao Liu;B. Zang;Mahdi Azarpeyvand - 通讯作者:
Mahdi Azarpeyvand
Application of Phase-Averaging to Propeller Aeroacoustics
相位平均在螺旋桨气动声学中的应用
- DOI:
10.2514/6.2024-3316 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Ismaeel Zaman;Michele Falsi;B. Zang;Mahdi Azarpeyvand - 通讯作者:
Mahdi Azarpeyvand
Aeroacoustic Characteristics of a Strut-braced High-lift Device
支柱支撑高升力装置的气动声学特性
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:5.6
- 作者:
L. Bowen;Hasan Kamliya Jawahar;Mahdi Azarpeyvand - 通讯作者:
Mahdi Azarpeyvand
Mahdi Azarpeyvand的其他文献
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{{ truncateString('Mahdi Azarpeyvand', 18)}}的其他基金
Fundamental Understanding of Turbulent Flow over Fluid-Saturated Complex Porous Media
对流体饱和复杂多孔介质上湍流的基本理解
- 批准号:
EP/W033550/1 - 财政年份:2023
- 资助金额:
$ 87.22万 - 项目类别:
Research Grant
Groundbreaking tools and models to reduce air pollution in urban areas
减少城市地区空气污染的开创性工具和模型
- 批准号:
EP/X02797X/1 - 财政年份:2023
- 资助金额:
$ 87.22万 - 项目类别:
Research Grant
Aerodynamics and aeroacoustics of turbulent flows over and past permeable rough surfaces
穿过可渗透粗糙表面的湍流的空气动力学和气动声学
- 批准号:
EP/S013024/1 - 财政年份:2019
- 资助金额:
$ 87.22万 - 项目类别:
Research Grant
JINA: Jet Installation Noise Abatement
JINA:喷射装置噪音消除
- 批准号:
EP/S000917/1 - 财政年份:2019
- 资助金额:
$ 87.22万 - 项目类别:
Research Grant
Effect of Separation and Stall on Aerofoil Noise
分离和失速对机翼噪声的影响
- 批准号:
EP/R010846/1 - 财政年份:2018
- 资助金额:
$ 87.22万 - 项目类别:
Research Grant
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相似海外基金
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开发基于集群的动态失速流最优反馈控制降阶模型
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