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Nonlinear Dynamic Loadings and Responses for Wind Turbine Reliability

Nonlinear Dynamic Loadings and Responses for Wind Turbine Reliability
风力发电机可靠性的非线性动态载荷和响应
批准号:
0933292
负责人:
Brian Feeny
金额:
$28.03万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-08-15 至 2013-07-31

项目摘要

项目成果

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中文摘要
翻译
0933292Feeny项目摘要随着风力涡轮机尺寸的增加,其可靠性和维护方面的挑战也随之增加。随着风力涡轮机的大型化,齿轮箱轴承故障变得更加频繁,通常早于轴承的设计寿命。这意味着载荷和失效机制还没有被充分理解,以帮助设计过程。很可能存在未知的动态载荷情况。智力优势:这项工作的目的是提高风力涡轮机叶片载荷的理解,以及它们如何转化为齿轮箱上的载荷。叶片上的载荷可以以各种方式引起振荡。叶片中的振动意味着动态载荷传递到齿轮箱。了解这些动态载荷对于设计可靠的齿轮和轴承以及经济可行的风力涡轮机至关重要。这项工作将涉及非线性扰动分析的共振和稳定性的降阶,非线性模型的叶片。所识别的共振将为模拟包(如FAST、Romax和Mackack模拟)提供测试用例参数。降阶非线性摄动分析的好处是:(1)识别共振作为参数的函数。这为选择模拟包中的参数提供了指导。(2)识别“非预期”共振,如次谐波、超谐波和滞后初级和次级共振。其中一些共振可能具有取决于初始条件的共存稳定解,或者可能与“危险”分叉相关。该模型包括非线性刚度和混合非线性(速度,加速度和位移),直接激励和参数激励作用于非线性项,由于循环气动载荷和重力载荷。降阶模型将比模拟包更粗糙,但将导致将行为与参数相关联的解析表达式,并且将指导用于更高保真度模拟的参数选择。因此,非线性研究将有助于未来的高保真仿真。更广泛的影响:由此产生的轴承设计改进将延长轴承寿命,减少维护工作和相关的巨大成本。这将有助于克服目前阻碍风力涡轮机行业充分发挥其潜力的一个重要问题。因此,结果将提供给NREL齿轮箱可靠性协作。该项目将培养一名风力涡轮机动力学和设计方面的博士生。该项目还将支持本科生研究人员,使高年级本科生接触研究。代表性不足的少数民族和妇女将通过斯隆计划和密歇根州立大学AAGA计划寻求。PI将增加风力涡轮机动力学,他在密歇根州立大学数学科学与技术暑期机械工程类中学生的参与。
英文摘要
0933292FeenyProject SummaryAs wind turbines increase in size, challenges in their reliability and maintenance increase. With the larger wind turbines, gearbox bearing failures become more frequent, often well before the designed life of the bearing. This means that loadings, and failure mechanisms, are not yet sufficiently understood to help the design process. It is likely that there exist unknown dynamical loading cases. Intellectual Merits: The aim of this work is to improve the understanding of wind-turbine blade loadings and how they translate to loadings on the gearbox. Loadings on the blades can induce oscillations in a variety of ways. Oscillations in the blades imply dynamic loadings transferred to the gearbox. Understanding these dynamic loadings is essential to the design of reliable gears and bearings, and hence economically viable wind turbines. This work will involve nonlinear perturbation analysis of resonances and stabilities on reduced-order, nonlinear models of the blades. The identified resonances would provide test case parameters for simulation packages such as FAST, Romax, and Simpack simulations. The benefits of reduced-order nonlinear perturbation analysis are (1) the identification resonances as functions of parameters. This gives guidelines for choosing parameters in simulations packages. (2) the identification of "unexpected" resonances, such as subharmonics, superharmonics, and hysteretic primary and secondary resonances. Some of these resonances may have coexisting stable solutions that depend on initial conditions, or could be associated with "dangerous" bifurcations. The modeling includes nonlinear stiffness and mixed nonlinearity (velocity, acceleration, and displacements), direct excitations and parametric excitations acting on nonlinear terms, due to cyclic aerodynamic loading and gravitational loading. The reduced order model will be coarser than simulation packages, but will lead to analytic expressions relating behavior to parameters, and will guide parameter choices for higher fidelity simulations. So the nonlinear studies will assist future, high fidelity simulations.Broader Impacts: The resulting improvements in bearing designs will lengthen the bearing life, and reduce maintenance efforts, and the associated enormous costs. This will help overcome one important issue that currently impedes the wind turbine industry from reaching its full potential. As such, results will be made available to the NREL Gearbox Reliability Collaborative. The project will train a doctoral student on wind turbine dynamics and design. The project will also support undergraduate researchers, exposing advanced undergraduates to research. Under-represented minorities and women will be sought through the Sloan program and the MSU AAGA program. The PI will add wind-turbine dynamics to his participation in an MSU Mathematics Science and Technology summer Mechanical Engineering class for middle schoolers.
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Vertical-Axis Wind Turbine Blade Vibration Modeling for Improved Reliability
  • 批准号:
    1435126
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2014
  • 负责人:
    Brian Feeny
  • 依托单位:
Coupled Blade-Hub Dynamics in Large Horizontal-Axis Wind Turbines
  • 批准号:
    1335177
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.0万
  • 财政年份:
    2013
  • 负责人:
    Brian Feeny
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A Positive Effect of Negative Stiffness: Wave Behavior and Energy Management
  • 批准号:
    1030377
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.96万
  • 财政年份:
    2010
  • 负责人:
    Brian Feeny
  • 依托单位:
Modal Identification by Decomposition Methods
  • 批准号:
    0727838
  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.0万
  • 财政年份:
    2007
  • 负责人:
    Brian Feeny
  • 依托单位:
国内基金
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Dynamic Credit Rating with Feedback Effects
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  • 项目类别:
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  • 资助金额:
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    2024
  • 负责人:
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  • 依托单位: