Collaborative Research: Scaling of Unsteady Locomotor Performance and Maneuverability

鲸鱼是最大的动物，必须能够在它们的水生环境中机动以捕获猎物，避开捕食者，在复杂的环境中航行，并竞争配偶。机动的能力（例如，加速，快速和紧密地转向）通常随着质量的增加而减少，这表明操纵水生动物的尺寸有上限。 这项研究将评估海洋中最大的动物，虎鲸，在野外进行自然行为的可操作性的大小依赖性。放置在自由放养的鲸鱼身体上的定制设计的可移动传感器将记录它们的运动，而带有专用相机的空中无人机将测量鲸鱼及其附属物的大小和形状（即，鳍状肢、吸虫）在水面上。通过将这些数据与水动力的数学建模相结合，可以比较不同大小的鲸鱼物种，以确定由大小作为世界生态和进化驱动力所施加的机械约束。最大的掠食者。该项目将包括培养研究生和博士后学者进行跨学科研究，将工程学和物理学与生物学相结合。 此外，研究结果可为自主水下航行器的仿生设计提供见解，以增强操纵性能。运动是动物生活的一个基本方面。量化个体的精细运动对于理解生理、生态和进化过程具有重要意义。机动能力也是至关重要的，因为它决定了动物捕捉猎物，避开捕食者和障碍物，栖息在复杂环境中以及竞争配偶的能力。对动物如何在水生环境中机动的调查仍然知之甚少，特别是对于处于动物体重极限的大型动物。该建议开发了一种生物记录和遥感方法，与计算建模，分析的运动学和机动性的自由放养的rorqual鲸鱼（Balaenopteridae）的身体质量范围内的一个数量级。游泳成绩（即，加速度：游泳速度的变化;敏捷性：旋转速度机动性：转弯半径）将随着身体大小的增加而减少，并且这些由形态大小施加的机械约束将明显地作为世界上最大的捕食者的生态和进化的驱动力。定制工程多传感器动物携带的标签和流体透镜相机连接到空中无人机将被用来分析在开放的海洋中的运动学和形态学。这种方法使我们能够量化的高分辨率运动学的rorquals从事自然演习，同时量化的标记的动物，包括控制和推进表面的形态尺寸。通过将这些数据与建模相结合，可以通过计算流体动力学（CFD）和轨迹计算水动力

Whales, the largest animals, must be able to maneuver in their aquatic environment to capture prey, avoid predators, navigate complex environments, and compete for mates. The ability to maneuver (e.g., accelerate, turn quickly and tightly) generally decreases as mass increases, suggesting there is an upper size limit for maneuvering aquatic animals. This study will evaluate the size dependence of maneuverability of the largest animals in the ocean, rorqual whales, performing natural behaviors in the wild. Custom-designed removable sensors placed on the bodies of free-ranging whales will record their movement while aerial drones with specialized cameras will measure the size and shape of the whales and their appendages (i.e., flippers, flukes) at the surface of the water. By combining these data with mathematical modeling of hydrodynamic forces, different sized whale species can be compared to determine mechanical constraints imposed by size as a driving force in the ecology and evolution of the world?s largest predators. This project will include the training of graduate students and postdoctoral scholars in interdisciplinary research that integrates engineering and physics with biology. Further, the results may provide insights into the biomimetic design of autonomous underwater vehicles with enhanced maneuvering performance. Movement is a fundamental aspect of animal life. Quantifying the fine-scale movement of individuals has important consequences for understanding physiological, ecological, and evolutionary processes. Maneuvering capacity is also critically important as it governs an animal's ability to capture prey, avoid predators and obstacles, inhabit complex environments, and compete for mates. Investigations into how animals maneuver in aquatic environments remains poorly understood, particularly for large animals at the extreme of animal body mass. This proposal develops a bio-logging and remote sensing approach, with computational modeling, to analyze the kinematics and maneuverability of free-ranging rorqual whales (Balaenopteridae) ranging in body mass by an order of magnitude. Swimming performance (i.e., acceleration: change in swimming velocity; agility: rate of turning; maneuverability: turning radius) will decrease as body size increases across rorqual species and that these mechanical constraints imposed by morphology size will be evident as a driving force in the ecology and evolution of the world's largest predators. Custom engineered multi-sensor animal-borne tags and Fluid Lensing cameras attached to aerial drones will be used to analyze the kinematics and morphology of rorquals in the open ocean. This approach enables us to quantify the high-resolution kinematics of rorquals engaged in natural maneuvers while simultaneously quantifying the morphological dimensions of tagged animal, including control and propulsion surfaces. By combining these data with modeling where hydrodynamic forces can be calculated via Computational Fluid Dynamics (CFD) and trajectories