Improving Swimming Performance and Flow Sensing by Incorporating Passive Mechanisms.
Degree: PhD, Mechanical Engineering, 2020, Clemson University
As water makes up approximately 70% of the Earth's surface, humans have expanded operations into aquatic environments out of both necessity and a desire to gain potential innate benefits. This expansion into aquatic environments has consequently developed a need for cost-effective and safe underwater monitoring, surveillance, and inspection, which are missions that autonomous underwater vehicles are particularly well suited for. Current autonomous underwater vehicles vastly underperform when compared to biological swimmers, which has prompted researchers to develop robots inspired by natural swimmers. One such robot is designed, built, tested, and numerically simulated in this thesis to gain insight into the benefits of passive mechanisms and the development of reduced-order models.
Using a bio-inspired robot with multiple passive tails I demonstrate herein the relationship between maneuverability and passive appendages. I found that the allowable rotation angle, relative to the main body, of the passive tails corresponds to an increase in maneuverability. Using panel method simulations I determined that the increase in maneuverability was directly related to the change in hydrodynamic moment caused by modulating the circulation sign and location of the shed vortex wake. The identification of this hydrodynamic benefit generalizes the results and applies to a wide range of robots that utilize vortex shedding through tail flapping or body undulations to produce locomotion.
Passive appendages are a form of embodied control, which manipulates the fluid-robot interaction and analogously such interaction can be sensed from the dynamics of the body. Body manipulation is a direct result of pressure fluctuations inherent in the surrounding fluid flow. These pressure fluctuations are unique to specific flow conditions, which may produce distinguishable time series kinematics of the appendage. Using a bio-inspired foil tethered in a water tunnel I classified different vortex wakes with the foil's kinematic data. This form of embodied feedback could be used for the development of control algorithms dedicated to obstacle avoidance, tracking, and station holding.
Mathematical models of autonomous vehicles are necessary to implement advanced control algorithms such as path planning. Models that accurately and efficiently simulate the coupled fluid-body interaction in freely swimming aquatic robots are difficult to determine due, in part, to the complex nature of fluids. My colleagues and I approach this problem by relating the swimming robot to a terrestrial vehicle known as the Chaplygin sleigh. Using our novel technique we determined an analogous Chaplygin sleigh model that accurately represents the steady-state dynamics of our swimming robot. We additionally used the subsequent model for heading and velocity control in panel method simulations. This work was inspired by the similarities in constraints and velocity space limit cycles of the swimmer and the Chaplygin sleigh, which makes this…
Advisors/Committee Members: Phanindra Tallapragada, Ardalan Vahidi, Yue Wang, John Wagner.
Subjects/Keywords: Bio-inspiration; Flow sensing; Reduced order modeling; Robotics; Vortex shedding
to Zotero / EndNote / Reference
APA (6th Edition):
Pollard, B. (2020). Improving Swimming Performance and Flow Sensing by Incorporating Passive Mechanisms. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2624
Chicago Manual of Style (16th Edition):
Pollard, Beau. “Improving Swimming Performance and Flow Sensing by Incorporating Passive Mechanisms.” 2020. Doctoral Dissertation, Clemson University. Accessed July 08, 2020.
MLA Handbook (7th Edition):
Pollard, Beau. “Improving Swimming Performance and Flow Sensing by Incorporating Passive Mechanisms.” 2020. Web. 08 Jul 2020.
Pollard B. Improving Swimming Performance and Flow Sensing by Incorporating Passive Mechanisms. [Internet] [Doctoral dissertation]. Clemson University; 2020. [cited 2020 Jul 08].
Available from: https://tigerprints.clemson.edu/all_dissertations/2624.
Council of Science Editors:
Pollard B. Improving Swimming Performance and Flow Sensing by Incorporating Passive Mechanisms. [Doctoral Dissertation]. Clemson University; 2020. Available from: https://tigerprints.clemson.edu/all_dissertations/2624