| Summary: | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 249-263). === Fish are equipped with a unique and elaborate flow sensing system, the lateral line, that enables them to reconstruct the near-field three-dimensional flow around their bodies, and hence effect precise control for optimal propulsion and to achieve energy recovery from vortical flows. This is a capability that is not available to engineered underwater systems today. A paradigm example lies in the ability of fish to save energy when swimming in schools, through extracting energy from vortices generated by other fish. For a single fish modeled as an undulating, foil-shaped body at Reynolds number Re=5000, swimming directly behind another fish results in energy savings of 15-20%, compared with swimming alone. This is achieved by properly timing the interaction with vortices generated from the upstream fish, as they travel along its body and tail. Fish that have evolved for sustained fast swimming, such as tunas and dolphins, possess a stiff tail that is morphologically separate from their body. For such fish, the phasing of tail motion is known to be important, and we demonstrate that independent and precise control of the tail is even more critical for flow control in the presence of external vortices. With an independently pitching caudal fin, small variations in phase can alter the energy savings by 15% or more, and precise timing can allow the fish to swim behind another fish with less than 50% of the energy required in quiescent water. We explore the flow mechanisms that lead to this remarkable performance and provide detailed flow visualization documenting the vorticity control effected by the independently pitching tail. We also show that the precise feedback control required to achieve this remarkable swimming performance is feasible using the distributed flow sensing provided by the lateral line. A model-based observer is shown to be capable of extracting the positions of near-field vortices using distributed surface pressure measurements, within an error of less than 1% of the body length. With this precise feedback, we show that the fish can lock in to the frequency of an upstream wake at the correct phase, and fine-tune its tail motion to optimally exploit the wake. This demonstrates that, together, distributed flow sensing and vorticity control provide a powerful tool to control the flow for enhanced swimming performance. === by Amy Ruiming Gao. === Ph. D.
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