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Modeling, Analysis, and Diagnostics of High Strength-to-Weight Wind Turbine Blades Using Tensegrity Principles

Modeling, Analysis, and Diagnostics of High Strength-to-Weight Wind Turbine Blades Using Tensegrity Principles
使用张拉整体原理对高强度重量比风力涡轮机叶片进行建模、分析和诊断
批准号:
1762825
负责人:
Raktim Bhattacharya
金额:
$37.47万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2022-08-31

项目摘要

项目成果

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中文摘要
翻译
在地球仪范围内获得负担得起、可靠和可持续的能源是联合国2030年的目标之一。这就需要大幅度增加可再生能源在全球能源组合中的份额。如果世界要实现这一目标,风能是解决方案的重要组成部分。为了实现2030年的目标,该行业正在转向可以部署更大风力涡轮机的离岸地点。随着转子变得更大,叶片变得更长,这带来了一些挑战。 该行业一直依赖于叶片结构设计、制造工艺和材料性能的改进,以满足对保持轻质、坚固和刚性的较长叶片的要求。目前,材料性能标准将纤维增强聚合物复合材料确定为转子叶片的主要候选材料。然而,这种材料的使用在设计分析、制造、振动控制、结构健康评估和运输方面提出了一些挑战。在这项工作中,研究人员将开发新的理论和计算工具,用于使用张拉整体原理设计大型涡轮机叶片,这将大大减轻上述工程挑战。预计所提出的设计框架将是破坏性的,并导致下一代风力涡轮机叶片的更有效的设计。风力涡轮机叶片的基于张拉整体的设计具有几个优点,包括精确建模、气动弹性剪裁、用于结构健康监测的最佳感测以及收缩到较小形状因子以便于部署的能力。拟议的研究将缓解风能界面临的一些紧迫的技术和科学挑战,并为解决从2012年的5吉瓦到2030年的150吉瓦的拟议扩张提供可行的途径。在这项研究中将解决的科学问题也提出了一个新的系统工程的角度来看,这是在目前的工程实践中缺失。每个组件技术(基于物理/数据的建模,传感,驱动,控制,计算)的最新技术已经相当成熟。然而,缺乏系统的视角。通常,这些系统首先被构建和建模,感测和致动架构(包括精度)以自组织方式被决定,随后是由该自组织感测和控制架构约束的估计/控制律的设计。在这项工作中,我们追求结构(质量特性,拓扑结构,动力学)和传感架构(用于最佳健康监测)的综合设计方法,这提供了一个具有强大理论基础的新视角。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Access to affordable, reliable, and sustainable energy across the globe is one of the 2030 targets of the United Nations. This requires a substantial increase in the share of renewable energy within the global energy mix. Wind is a prominent part of the solution if the world is to achieve such a target. To meet the 2030 target, the industry is moving to off-shore sites where larger wind-turbines can be deployed. As the rotors become larger, the blades become longer which poses some challenges. The industry has relied on improvements in blade structural design, manufacturing processes and material properties to meet the requirements for longer blades that remain light-weight, strong and stiff. Currently, material performance criteria identify fiber-reinforced polymer composites as the prime candidate for rotor blades. However, use of such material presents several challenges in design analysis, manufacturing, vibration control, structural health assessment, and transportation. In this effort, the investigators will develop new theoretical and computational tools for designing large turbine blades using tensegrity principles, which will significantly alleviate some of the above described engineering challenges. It is expected that the proposed design framework will be disruptive and lead to much more efficient design of next generation wind-turbine blades. The tensegrity-based design of wind-turbine blades has several advantages including accurate modeling, aero-elastic tailoring, optimal sensing for structural health monitoring, and ability to contract to a smaller form factor for easy deployability. The proposed research will alleviate some of the pressing technical and scientific challenges in the wind energy community, and provide a feasible path to address the proposed expansion from 5 GW in 2012 to 150 GW in 2030. The scientific problems that will be addressed in this research also present a new systems engineering perspective, which is missing in current engineering practices. The state-of-the-art in each component technology (physics/data based modeling, sensing, actuation, control, computation) is quite matured. However, a systems perspective is missing. Typically these systems are first built and modeled, sensing and actuation architecture (including precision) is decided in an adhoc manner, followed by the design of the estimation/control law that is constrained by this adhoc sensing and control architecture. In this effort, we pursue an integrated approach for design of the structure (mass properties, topology, dynamics), and the sensing architecture (for optimal health monitoring), which provides a new perspective with strong theoretical foundations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
Data-driven Solution of Stochastic Differential Equations Using Maximum Entropy Basis Functions
使用最大熵基函数的随机微分方程的数据驱动解
DOI: --
发表时间: 2020
期刊: IFAC World Congress
影响因子: --
作者: [Deshpande, Vedang, Bhattacharya, Raktim]
通讯作者: Bhattacharya, Raktim
DOI: 10.23919/acc50511.2021.9483377
发表时间: 2021-03
期刊: 2021 American Control Conference (ACC)
影响因子: --
作者: [Vedang M. Deshpande;R. Bhattacharya]
通讯作者: Vedang M. Deshpande;R. Bhattacharya
Surrogate Modeling of Dynamics From Sparse Data Using Maximum Entropy Basis Functions
使用最大熵基函数从稀疏数据进行动力学代理建模
DOI: 10.23919/acc45564.2020.9147384
发表时间: 2020
期刊: American Control Conference
影响因子: --
作者: [Deshpande, Vedang M., Bhattacharya, Raktim]
通讯作者: Bhattacharya, Raktim
DOI: 10.1109/lcsys.2020.3001490
发表时间: 2021-01
期刊: IEEE Control Systems Letters
影响因子: 3
作者: [Sunsoo Kim;Vedang M. Deshpande;R. Bhattacharya]
通讯作者: Sunsoo Kim;Vedang M. Deshpande;R. Bhattacharya
8
    I-Corps: Multi-axis Deformable Sensor/Actuator System
    CCF: SHF: EAGER:Collaborative:Asynchronous Algorithms for Exascale Computing Systems
    CSR: Small: Uncertainty Management in Real-Time Embedded Control Systems
    CSR---CPS: Design of Robust and Energy Efficient Cyber-Physical Systems Using Dynamical Systems and Control Theory
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Intelligent Patent Analysis for Optimized Technology Stack Selection:Blockchain BusinessRegistry Case Demonstration
    • 批准号:
      --
    • 项目类别:
      外国学者研究基金项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      USHARANI HAREESH GOVINDARA JAN
    • 依托单位:
    基于Meta-analysis的新疆棉花灌水增产模型研究
    • 批准号:
      41601604
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      22.0万元
    • 批准年份:
      2016
    • 负责人:
      赵爱琴
    • 依托单位:
    大规模微阵列数据组的meta-analysis方法研究
    • 批准号:
      31100958
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      20.0万元
    • 批准年份:
      2011
    • 负责人:
      赵洪雅
    • 依托单位: