Breakdown of helical vortices in wind farms
风电场螺旋涡的分解
基本信息
- 批准号:EP/M025039/1
- 负责人:
- 金额:$ 12.54万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2015
- 资助国家:英国
- 起止时间:2015 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The project investigates developments of helical vortices shed from tips of wind turbines and ubiquitously observed in offshore wind farms. The instabilities and breakdown of these vortices are critical to the development of the wake flow and consequently impose significant impacts on downstream wind turbines in terms of fatigue loading, lifetime and acoustic noise. Better understanding of the dynamics of helical vortices will lead to more advanced methods in wind turbine design and wind farm layout, more accurate predictions of wind turbine lifetime and energy generation of wind farms, and ultimately reduced price of wind energy. A better understanding of the dynamics of helical vortices will also be more generally useful, e.g. in aerodynamic performance of helicopter rotors or turbine impellers, erosion induced by tip-vortex cavitation in ship propellers, and breakdown of straight vortices. At present there are no general numerical tools to calculate the global stability of helical vortices and the breakdown of these vortices driven by instabilities. Most of the existing work on helical vortices concerns experimental measurements of vortex breakdown or analytical stability analyses using simplified models, e.g. inviscid and thin helical vortex filaments perturbed by either short or long waves. As a result, the path to understanding the role of instabilities in breakdown is blocked, and so also is the capability to design wind turbines and farms taking into account the effect of wake flow on performances. General numerical studies of global stabilities of helical vortices require a novel algorithm originating from classical stability theories, which have been used on straight vortices in both Cartesian and cylindrical frames. Such an algorithm to study helical vortices will be implemented in the Frenet frame, taking advantage of the homogeneity of the helical vortices in the vortex axis direction and therefore enabling the integration of existing stability theories across scales (from short-wave to long-wave) into one framework. Both theoretical models of helical vortices and experimentally measured mean flow in the wake of a turbine will be used as the base flow in stability studies. The results will be cross-validated against field measurements and theoretically derived instabilities. Direct numerical simulations (DNS) of helical vortices initially perturbed by the most energetic modes will be conducted in the Frenet frame, which enables DNS at much larger Reynolds numbers than other frames. The simulations will reveal the role of various linear modes in the breakdown of helical vortices. The distribution of wind in the wake extracted from the simulation can be modeled as a more accurate alternative of the models used in current industry applications, e.g. the PARK model. This new model will be broadly useful in the design and operation of large-scale offshore wind farms, which require fast & precise predictions of the wake flow.
该项目研究了从风力涡轮机尖端脱落并在海上风电场中普遍观察到的螺旋涡流的发展。这些涡流的不稳定性和破坏对于尾流的发展至关重要,因此对下游风力涡轮机的疲劳载荷、寿命和声学噪声产生重大影响。更好地了解螺旋涡的动力学将有助于在风力发电机设计和风电场布局方面采用更先进的方法,更准确地预测风力发电机的寿命和风电场的发电量,并最终降低风能的价格。更好地理解螺旋涡流的动力学也将更普遍有用,例如直升机旋翼或涡轮叶轮的空气动力学性能、船舶螺旋桨中尖涡空化引起的侵蚀以及直涡的破坏。目前还没有通用的数值工具来计算螺旋涡旋的整体稳定性以及由不稳定性驱动的这些涡旋的分解。大多数关于螺旋涡流的现有工作涉及涡流破裂的实验测量或使用简化模型的分析稳定性分析,例如无粘性且细的螺旋涡丝,受到短波或长波的扰动。结果,理解不稳定性在故障中的作用的途径被阻碍,设计风力涡轮机和发电场时考虑尾流对性能的影响的能力也被阻碍。螺旋涡旋全局稳定性的一般数值研究需要一种源自经典稳定性理论的新颖算法,该算法已用于笛卡尔坐标系和圆柱坐标系中的直涡旋。这种研究螺旋涡的算法将在 Frenet 框架中实现,利用螺旋涡在涡轴方向上的均匀性,从而能够跨尺度(从短波到长波)集成现有的稳定性理论到一个框架中。螺旋涡流的理论模型和实验测量的涡轮尾流平均流量都将用作稳定性研究的基础流量。结果将根据现场测量和理论上得出的不稳定性进行交叉验证。最初受到最高能模式扰动的螺旋涡流的直接数值模拟(DNS)将在 Frenet 框架中进行,这使得 DNS 的雷诺数比其他框架大得多。模拟将揭示各种线性模式在螺旋涡流破裂中的作用。从模拟中提取的尾流中风的分布可以建模为当前工业应用中使用的模型的更准确的替代方案,例如,公园模型。这种新模型将广泛用于需要快速、精确预测尾流的大型海上风电场的设计和运营。
项目成果
期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
New method to capture traveling waves in flow passing a wind turbine
捕获流过风力涡轮机的流中行波的新方法
- DOI:10.1002/we.2331
- 发表时间:2019
- 期刊:
- 影响因子:4.1
- 作者:Le Clainche S
- 通讯作者:Le Clainche S
Optimal transient growth on a vortex ring and its transition via cascade of ringlets
涡环上的最佳瞬时生长及其通过小环级联的转变
- DOI:10.1017/jfm.2017.675
- 发表时间:2017
- 期刊:
- 影响因子:3.7
- 作者:Mao X
- 通讯作者:Mao X
Coherent Structures in the Breakdown Bubble of a Vortex Flow
涡流破裂气泡中的相干结构
- DOI:10.2514/1.j055329
- 发表时间:2018
- 期刊:
- 影响因子:2.5
- 作者:Paterson O
- 通讯作者:Paterson O
Transition induced by linear and nonlinear perturbation growth in flow past a compressor blade
- DOI:10.1017/jfm.2017.240
- 发表时间:2017-05
- 期刊:
- 影响因子:3.7
- 作者:X. Mao;T. Zaki;S. Sherwin;H. Blackburn
- 通讯作者:X. Mao;T. Zaki;S. Sherwin;H. Blackburn
Sensitivity of forces to wall transpiration in flow past an aerofoil.
- DOI:10.1098/rspa.2015.0618
- 发表时间:2015-12-08
- 期刊:
- 影响因子:0
- 作者:Mao X
- 通讯作者:Mao X
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Xuerui Mao其他文献
Low-frequency selectivity in flat-plate boundary layer with elliptic leading edge
椭圆前缘平板边界层的低频选择性
- DOI:
10.1017/jfm.2019.91 - 发表时间:
2019-03 - 期刊:
- 影响因子:3.7
- 作者:
Bofu Wang;Xuerui Mao;Tamer Zaki - 通讯作者:
Tamer Zaki
Compressed neural networks for reduced order modeling
用于降阶建模的压缩神经网络
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Yin Zhu;Qiangqiang Sun;Dandan Xiao;Jie Yao;Xuerui Mao - 通讯作者:
Xuerui Mao
Non-modal growth of finite-amplitude disturbances in oscillatory boundary layer
振荡边界层中有限振幅扰动的非模态增长
- DOI:
10.1017/jfm.2022.446 - 发表时间:
2022-06 - 期刊:
- 影响因子:3.7
- 作者:
Minjiang Gong;Chengwang Xiong;Xuerui Mao;Liang Cheng;Shi-Ping Wang;A-Man Zhang - 通讯作者:
A-Man Zhang
Model reduction of travelling-wave problems via Radon cumulative distribution transform
通过氡累积分布变换对行波问题进行模型简化
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Jie Ren;William R. Wolf;Xuerui Mao - 通讯作者:
Xuerui Mao
Xuerui Mao的其他文献
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{{ truncateString('Xuerui Mao', 18)}}的其他基金
Breakdown of helical vortices in wind farms
风电场螺旋涡的分解
- 批准号:
EP/M025039/2 - 财政年份:2016
- 资助金额:
$ 12.54万 - 项目类别:
Research Grant
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基于“马鞍型”邻-四联噻吩为结构单元的螺旋状与树枝状噻吩低聚物的制备
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相似海外基金
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混合光学涡旋开创了先进螺旋材料
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螺旋涡的不稳定性和湍流转变研究
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21H01242 - 财政年份:2021
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Breakdown of helical vortices in wind farms
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