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Collaborative Research: Analysis and design of textured super-hydrophobic surfaces capable of preventing ice formation on wind turbine blades

Collaborative Research: Analysis and design of textured super-hydrophobic surfaces capable of preventing ice formation on wind turbine blades
合作研究:分析和设计能够防止风力涡轮机叶片结冰的纹理超疏水表面
批准号:
1336232
负责人:
Mehdi Raessi
金额:
$21.46万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2019-08-31

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中文摘要
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PI: Raessi, Mehdi / Lackner, MatthewProposal Number: 1336232 / 1336502Institution: University of Massachusetts, Dartmouth / University of Massachusetts AmherstTitle: Collaborative Research: Analysis and design of textured super-hydrophobic surfaces capable of preventing ice formation on wind turbine bladesWind energy is a clean, renewable, and domestic energy source that is abundant in the U.S., in particular in cold climates where ice formation is common. The potential to generate renewable wind energy in cold climates is immense, both in the U.S. and internationally. The current wind energy capacity in cold climates is only 500 MW, however, which is primarily due to the challenges posed by icing at these sites, which has numerous detrimental effects. Mitigation efforts to date have had moderate success at reducing ice accumulation, but reduce efficiency. The research objectives of this project are to better understand the physics of ice formation on wind turbine blades using advanced computational models, to investigate the aerodynamics of wind turbine airfoils and blades that utilize textured surfaces using computational fluid dynamics and a novel turbulence model, and finally to design and then valuate textured super-ice-phobic surfaces for wind turbine blades in order to prevent ice formation. The project aims at addressing the major issue of ice accretion on wind turbine blades by combining the expertise of PIs in wind turbine aerodynamics, turbulence modeling, and multiphase flows and solidification. The research on textured super-hydrophobic surfaces will have a transformative effect on wind energy development in cold climates by reducing ice formation, and thus increasing the turbine?s efficiency and reliability.This project will be the first study to investigate the performance of textured super-hydrophobic surfaces under real-world conditions, and the first to design textured super-ice-phobic surfaces that are specially engineered for the flow fields around wind turbine blades. By taking into account the local flow field around a blade in our computational simulations, we will optimally design texture patterns that may vary along a blade, depending on the relative velocity of the blade and water droplets, in order to achieve most effective super-ice-phobic surfaces. Furthermore, the CFD tool that will be utilized represents a significant advance over the current state of the art for analyzing wind turbine airfoil and blade aerodynamics. This work will create a computational framework that uses a turbulence model designed for the complex physics (including transition, separation, 3D boundary layers, and rotation) occurring on a wind turbine blade, particularly those with textured ice-phobic surfaces. These expected outcomes will provide the predictive capabilities that are necessary to analyze and design the unique ice-phobic blade surfaces that are capable of operating in cold environments, enabling increased development of wind energy in these regions.Accomplishing the research and student education objectives will benefit society via increased production of renewable energy in the U.S. and internationally. An international partnership with CanmetENERGY of Natural Resources Canada will result from this project, including data sharing and researcher interaction. Moreover, the research and education plans offer exciting opportunities to promote cross-campus collaboration among two campuses within the University of Massachusetts system. The participation of women and underrepresented minorities in engineering will be increased by the activities in this project. The computational tools developed in this project will be utilized in the Computer Girl Power summer camp at UMass Dartmouth. Undergraduate RAs will be recruited using the NSF-funded LSAMP program at UMass Amherst and from UMass Dartmouth?s diverse population of undergraduates, 40% of whom are underrepresented in the sciences. An extensive dissemination plan has been developed to educate the general public about issues of wind energy and icing in cold climates, including using public radio and YouTube.
期刊论文(1)
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会议论文
DOI: 10.1016/j.jcp.2023.111986
发表时间: 2023-02
期刊: J. Comput. Phys.
影响因子: --
作者: [Ashish Pathak;W. Jin;M. Raessi]
通讯作者: Ashish Pathak;W. Jin;M. Raessi
Collaborative Research: Integrated experimental and computational investigations of exogenous surfactant distribution in conducting zone lung airways
A comprehensive computational framework for analysis and optimization of wave energy converters
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)