CAREER: Uncovering the wake dynamics of high-frequency, asymmetric swimming and flying

职业：揭示高频、不对称游泳和飞行的尾流动力学

• 批准号: 2040351
• 负责人: Daniel Quinn
• 金额: $ 50万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2040351&HistoricalAwards=false
• 关键词: CAREER; Uncovering; wake; dynamics; frequency

Fish and birds use complex high-speed maneuvers when chasing prey or escaping predators. How water and air flow around these animals during maneuvers is mostly unknown. Mapping out these flows will help biologists better understand the relationship between fish, birds, and their environment. Mapping out these flows will help bio-inspired roboticists, who currently rely on models of low-speed, symmetric gaits when designing and testing robots. Understanding the flows that govern rapid maneuvers will enable a new generation of fast, flexible, ultra-maneuverable bio-inspired robots. The principal goal of this project is therefore to discover the fluid dynamics that govern high-speed, asymmetric swimming/flying gaits. The project integrates educational activities, including virtual tours where students from rural high schools teleconference into the lab and remotely control a robotic swimming rig.This project is made possible by a unique rig that creates high-frequency, asymmetric flapping motions in a water channel. The rig uses a scotch-yoke mechanism to double the frequencies traditionally available to studies of swimming and flying, and it floats on air bushings in order to simulate autonomous maneuvers. The performance of fish- and bird-inspired propulsion strategies are then quantified by a combination of Particle Image Velocimetry and dynamic force measurements. These experiments will inform adaptations to models of unsteady aerodynamics as they pertain to swimming and flying animals and robots. The experimental-theoretical campaign will focus on three specific research goals: (i) Determine what three-dimensional flow features govern the thrust and efficiency of high-frequency bio-inspired gaits, (ii) Determine what three-dimensional flow features govern the maneuverability of asymmetric bio-inspired gaits, and (iii) Determine what wake-driven models predict the performance of high-frequency, asymmetric, tunable-stiffness fins and wings. More generally, the project’s overarching goal is for the unique semiautonomous rig and the associated modeling to create new precedents and templates for those integrating fluid dynamics into the next generation of intelligent machines.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.

鱼类和鸟类在追逐猎物或逃避捕食者时会使用复杂的高速机动。水和空气如何在这些动物周围流动，在演习中大多是未知的。绘制这些流动将有助于生物学家更好地了解鱼类，鸟类和它们的环境之间的关系。绘制这些流程将有助于生物启发的机器人专家，他们目前在设计和测试机器人时依赖低速对称步态模型。了解控制快速机动的流动将使新一代快速，灵活，超可拆卸的生物启发机器人成为可能。因此，该项目的主要目标是发现控制高速，不对称游泳/飞行步态的流体动力学。该项目整合了教育活动，包括虚拟图尔斯之旅，来自农村高中的学生通过电话会议进入实验室，并远程控制机器人游泳装置。该项目是通过一种独特的装置实现的，该装置可以在水道中产生高频，不对称的拍打运动。该装置使用苏格兰轭机制，将传统上用于游泳和飞行研究的频率增加一倍，并漂浮在空气衬套上，以模拟自主机动。鱼和鸟的启发推进策略的性能，然后量化的粒子图像测速和动态力测量的组合。这些实验将为适应不稳定空气动力学模型提供信息，因为它们与游泳和飞行动物和机器人有关。实验-理论活动将集中在三个具体的研究目标：（i）确定什么样的三维流动特征支配高频生物启发步态的推力和效率，（ii）确定什么样的三维流动特征支配非对称生物启发步态的机动性，以及（iii）确定什么样的尾流驱动模型预测高频，非对称，可调刚度鳍和翼的性能。更广泛地说，该项目的总体目标是为独特的半自动钻机和相关建模，为那些将流体动力学集成到下一代智能机器中的人创造新的先例和模板。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。

项目成果

Streamwise and lateral maneuvers of a fish-inspired hydrofoil

• DOI: 10.1088/1748-3190/ac1ad9
• 发表时间: 2021-08
• 期刊: Bioinspiration & Biomimetics
• 影响因子: 3.4
• 作者: Q. Zhong;D. Quinn

Development of a Stingray-inspired High-Frequency Propulsion Platform with Variable Wavelength

• DOI: 10.1109/iros47612.2022.9981761
• 发表时间: 2022-10
• 期刊: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• 作者: Q. Zhong;Yicong Fu;Leo Liu;D. Quinn

Tunable stiffness enables fast and efficient swimming in fish-like robots

• DOI: 10.1126/scirobotics.abe4088
• 发表时间: 2021-08-11
• 期刊: SCIENCE ROBOTICS
• 影响因子: 25
• 作者: Zhong, Q.;Zhu, J.;Quinn, D. B.
• 通讯作者: Quinn, D. B.

Fine-tuning near-boundary swimming equilibria using asymmetric kinematics

• DOI: 10.1088/1748-3190/aca131
• 发表时间: 2022-11
• 期刊: Bioinspiration & Biomimetics
• 影响因子: 3.4
• 作者: Leo Liu;Q. Zhong;Tianjun Han;K. Moored;D. Quinn