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

项目负责人：Raessi， Mehdi / Lackner， matthew提案编号：1336232 / 1336502机构：马萨诸塞大学达特茅斯分校/马萨诸塞大学阿默斯特分校标题：合作研究：能够防止风力涡轮机叶片结冰的纹理超水表面的分析和设计风能是一种清洁，可再生的国内能源，在美国是丰富的，特别是在寒冷气候中，冰的形成是常见的。无论是在美国还是在国际上，在寒冷气候下生产可再生风能的潜力都是巨大的。然而，目前在寒冷气候下的风能容量只有500兆瓦，这主要是由于这些地点的结冰带来的挑战，这有许多有害的影响。迄今为止的减缓努力在减少冰积方面取得了一定的成功，但降低了效率。该项目的研究目标是利用先进的计算模型更好地了解风力涡轮机叶片上结冰的物理特性，利用计算流体动力学和新型湍流模型研究利用纹理表面的风力涡轮机翼型和叶片的空气动力学，最后设计并评估用于风力涡轮机叶片的纹理超疏冰表面，以防止结冰。该项目旨在通过结合pi在风力涡轮机空气动力学、湍流建模、多相流和凝固方面的专业知识，解决风力涡轮机叶片上冰积聚的主要问题。对纹理超疏水表面的研究将对寒冷气候下的风能开发产生变革性影响，减少冰的形成，从而增加涡轮机？S效率和可靠性。该项目将是第一个在现实条件下研究纹理超疏水表面性能的研究，也是第一个设计为风力涡轮机叶片周围流场专门设计的纹理超疏冰表面的研究。通过在我们的计算模拟中考虑叶片周围的局部流场，我们将根据叶片和水滴的相对速度，优化设计沿着叶片变化的纹理图案，以获得最有效的超疏冰表面。此外，将使用的CFD工具代表了在分析风力涡轮机翼型和叶片空气动力学方面的当前艺术状态的重大进步。这项工作将创建一个计算框架，使用为风力涡轮机叶片上发生的复杂物理（包括过渡、分离、3D边界层和旋转）设计的湍流模型，特别是那些具有纹理疏冰表面的湍流模型。这些预期结果将为分析和设计独特的疏冰叶片表面提供必要的预测能力，这些叶片表面能够在寒冷环境中运行，从而促进这些地区风能的发展。完成研究和学生教育目标将通过增加美国和国际可再生能源的生产来造福社会。该项目将与加拿大自然资源部CanmetENERGY建立国际合作伙伴关系，包括数据共享和研究人员互动。此外，研究和教育计划为促进马萨诸塞大学系统内两个校区之间的跨校园合作提供了令人兴奋的机会。本项目的活动将增加妇女和代表性不足的少数民族对工程的参与。在这个项目中开发的计算工具将在马萨诸塞大学达特茅斯分校的计算机女孩力量夏令营中使用。本科生RAs将在马萨诸塞大学阿默斯特分校和马萨诸塞大学达特茅斯分校使用nsf资助的LSAMP项目招募。美国的本科生人口多样化，其中40%的人在科学领域的代表性不足。已经制定了一项广泛的传播计划，包括利用公共广播电台和YouTube，教育公众关于寒冷气候下的风能和结冰问题。

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.