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不协调拍打游泳者之间的流动相互作用产生群体凝聚力。

Flow interactions between uncoordinated flapping swimmers give rise to group cohesion.

机构信息

Applied Math Lab, Courant Institute, New York University, New York, NY 10012.

Department of Physics, New York University, New York, NY 10003.

出版信息

Proc Natl Acad Sci U S A. 2019 Feb 12;116(7):2419-2424. doi: 10.1073/pnas.1816098116. Epub 2019 Jan 30.

Abstract

Many species of fish and birds travel in groups, yet the role of fluid-mediated interactions in schools and flocks is not fully understood. Previous fluid-dynamical models of these collective behaviors assume that all individuals flap identically, whereas animal groups involve variations across members as well as active modifications of wing or fin motions. To study the roles of flapping kinematics and flow interactions, we design a minimal robotic "school" of two hydrofoils swimming in tandem. The flapping kinematics of each foil are independently prescribed and systematically varied, while the forward swimming motions are free and result from the fluid forces. Surprisingly, a pair of uncoordinated foils with dissimilar kinematics can swim together cohesively-without separating or colliding-due to the interaction of the follower with the wake left by the leader. For equal flapping frequencies, the follower experiences stable positions in the leader's wake, with locations that can be controlled by flapping amplitude and phase. Further, a follower with lower flapping speed can defy expectation and keep up with the leader, whereas a faster-flapping follower can be buffered from collision and oscillate in the leader's wake. We formulate a reduced-order model which produces remarkable agreement with all experimentally observed modes by relating the follower's thrust to its flapping speed relative to the wake flow. These results show how flapping kinematics can be used to control locomotion within wakes, and that flow interactions provide a mechanism which promotes group cohesion.

摘要

许多鱼类和鸟类以群体形式迁徙,但群体中流体相互作用的作用机制仍不完全清楚。先前关于这些集体行为的流体动力学模型假设所有个体的拍打动作都是完全相同的,而动物群体中个体之间存在差异,以及翅膀或鳍片运动的主动调整。为了研究拍打运动学和流场相互作用的作用,我们设计了一个由两个水翼组成的最小化机器人“群体”,它们以串联的方式游泳。每个水翼的拍打运动学都是独立规定并系统改变的,而前进的游动运动则是自由的,是由流体力产生的。令人惊讶的是,一对具有不同运动学特征的不协调水翼可以协同游动——不会分离或碰撞——这是由于跟随者与领导者留下的尾流之间的相互作用。对于相等的拍打频率,跟随者在领导者的尾流中处于稳定的位置,其位置可以通过拍打幅度和相位来控制。此外,一个拍打速度较慢的跟随者可以违背预期并跟上领导者,而一个拍打速度较快的跟随者可以免受碰撞并在领导者的尾流中振荡。我们提出了一个简化模型,通过将跟随者的推力与其相对于尾流的拍打速度相关联,该模型可以产生与所有实验观察到的模式的显著一致性。这些结果表明,拍打运动学可以用于控制尾流中的运动,并且流场相互作用提供了一种促进群体凝聚力的机制。

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