CAREER: Controlling fluid structure interactions within an oscillating foil turbine array

摆动翼片，或同时经历旋转和升起运动的机翼，是动物拍打飞行或水上推进的物理模型。受这些生物系统的启发，这项提议探索了一种振荡箔，它作为涡轮机运行，从河流或潮汐水道中获取动能。具体地说，这项研究将调查紧密堆积的振荡箔阵列中的非定常流动物理，并揭示提高功率生产的方法。这些知识将推动海洋能源涡轮机的开发，这是一种与风电场和太阳能发电场相辅相成的可再生能源技术。教育计划的更广泛影响旨在覆盖整个学术渠道的学生，改善可再生能源和机械行业女性的招聘和留住。摆动翼片的高升沉和俯仰运动产生了一个二维涡尾迹，其结构与拍动运动学复杂地联系在一起。作为一个额外的好处，振动箔可以主动地调节扫掠流动的面积，并与相邻和互补的箔片共享该扫掠面积，以提高能量密度。尽管有这些运动学上的优势，但关于翼片簇内运动学的主动控制的研究还很少。这项研究将利用与强化学习相结合的计算模型来与非定常尾迹环境相互作用，并阐明在一个由3到4个翼片组成的紧密分组中的涡动力学和协作控制的构造机制。这将通过与强化学习算法交织在一起的先进计算方法来执行，该算法能够探索非平凡的振荡运动学，并在非稳定流入条件下开发能量潜力。所提出的工作结果将为紧密聚集的振荡翼内的非定常流动物理提供一个框架，提高效率和能量密度，并改进用于非理想流动条件下的协调控制的建模和设计工具。教育目标将利用具体活动来改善女性本科生和研究生的招聘、留住和氛围，并为K-12外联开发可再生能源模块。通过新的新生设计课程、本科生研究和通过学生团体进行有针对性的指导工作，促进了研究和教育的整合。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

An oscillating foil, or a wing undergoing a combined rotational and heaving motion, is a physical model of flapping animal flight or aquatic propulsion. Inspired by these biological systems, this proposal explores an oscillating foil operating as a turbine to harvest kinetic energy from rivers or tidal channels. Specifically, this research will investigate the unsteady flow physics within a close-packed array of oscillating foils and uncover methods for enhanced power production. This knowledge will advance marine energy turbine development, a renewable energy technology complementary to wind and solar farms. The broader impacts of the education plan are designed to reach students throughout the academic pipeline, improving recruitment and retention of women in renewable energy and mechanics. The high heave and pitch kinematic motion of an oscillating foil generates a two-dimensional vortex wake whose structure is intricately linked to the flapping kinematics. As an additional benefit, oscillating foils can actively modulate the area of swept flow and share this swept area with adjacent and complementary foils to boost energy density. Despite these kinematic advantages, there has been little research on active control of kinematics within clusters of foils. This research will utilize a computational model combined with reinforcement learning to interact with the unsteady wake environment and elucidate constructive mechanisms for vortex dynamics and cooperative control within a tightly grouped cluster of 3 to 4 foils. This will be performed through an advanced computational methodology interwoven with a reinforcement learning algorithm that enables exploration of nontrivial oscillation kinematics and exploitation of the energy potential in unsteady inflow conditions. Results of the proposed work will develop a framework for the unsteady flow physics within tightly clustered oscillating foils, improving efficiency and energy density, and improving modeling and design tools for coordinated control in non-ideal flow conditions. The educational objectives will utilize specific activities to improve recruitment, retention, and climate for women undergraduate and graduate students, and develop renewable energy modules for K-12 outreach. Integration of research and education is facilitated through a new freshmen design course, undergraduate research, and targeted mentoring efforts through student groups.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.