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

摆动的翼片，或经历旋转和起伏运动的翅膀，是动物拍打飞行或水生推进的物理模型。受这些生物系统的启发，该方案探索了一种振荡箔作为涡轮机，从河流或潮汐通道中获取动能。具体来说，本研究将研究振荡箔紧密排列中的非定常流物理，并揭示增强功率生产的方法。这些知识将推动海洋能源涡轮机的发展，这是一种与风能和太阳能农场互补的可再生能源技术。教育计划的更广泛影响旨在影响整个学术管道的学生，改善可再生能源和机械领域的女性招聘和保留。振荡翼的高升沉和高俯仰运动产生二维旋涡尾迹，其结构与扑动运动有着复杂的联系。作为一个额外的好处，振荡箔可以主动调节扫流的面积，并与相邻和互补的箔共享这个扫流面积，以提高能量密度。尽管有这些运动学的优点，很少有研究主动控制的运动在集群的箔。本研究将利用结合强化学习的计算模型来与非定常尾流环境相互作用，并阐明在3到4个箔片紧密分组的集群中涡动力学和协同控制的建设性机制。这将通过先进的计算方法与强化学习算法相结合来实现，该算法可以探索非平凡的振荡运动学并利用非定常流入条件下的能量潜力。所提出的工作结果将为紧密聚集振荡箔内的非定常流动物理建立一个框架，提高效率和能量密度，改进非理想流动条件下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生、留用和氛围，并为K-12的推广开发可再生能源模块。通过新生设计课程、本科生研究和学生团体有针对性的指导工作，促进了研究和教育的整合。该奖项反映了美国国家科学基金会的法定使命，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。

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.