Tuna robotics: hydrodynamics of rapid linear accelerations

Abstract

Fish routinely accelerate during locomotor manoeuvres, yet little is known about the dynamics of acceleration performance. Thunniform fish use their lunate caudal fin to generate lift-based thrust during steady swimming, but the lift is limited during acceleration from rest because required oncoming flows are slow. To investigate what other thrust-generating mechanisms occur during this behaviour, we used the robotic system termed Tunabot Flex, which is a research platform featuring yellowfin tuna-inspired body and tail profiles. We generated linear accelerations from rest of various magnitudes (maximum acceleration of 3.22 m s − 2 at 11.6 Hz tail beat frequency) and recorded instantaneous electrical power consumption. Using particle image velocimetry data, we quantified body kinematics and flow patterns to then compute surface pressures, thrust forces and mechanical power output along the body through time. We found that the head generates net drag and that the posterior body generates significant thrust, which reveals an additional propulsion mechanism to the lift-based caudal fin in this thunniform swimmer during linear accelerations from rest. Studying fish acceleration performance with an experimental platform capable of simultaneously measuring electrical power consumption, kinematics, fluid flow and mechanical power output provides a new opportunity to understand unsteady locomotor behaviours in both fishes and bioinspired aquatic robotic systems.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 17, 2021
Source ID
10.1098/rspb.2020.2726

Entities

People

  • Carl White
  • George V. Lauder
  • Hilary Bart-Smith
  • Robin Thandiackal

Organizations

  • David and Lucile Packard Foundation
  • Harvard University
  • Office of Naval Research
  • Swiss National Science Foundation
  • University of Virginia

Tags

Readers

  • Fluid Mechanics and Fluid Dynamics.
  • Pulsed Power and Plasma Physics.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy
  • Biotechnology