Understanding why fish move the way in which they do has applications far outside of biology. Biological propulsion has undergone millions of years of refinement, far outpacing the capabilities of anything created by man. Research in the areas of unsteady/biological propulsion has been increasing in the last several decades with advances in technology. Researchers are currently conducting experiments using pitching and heaving airfoils, mechanized fish, and numerical fish. However, the surrogate propulsors that are being used in experiments are driven analytically, whereas in this study, a method has been developed to exactly follow the motion of swimming fish.
The research described in this thesis couples the image analysis of swimming fish with computational fluid dynamics to accurately simulate a virtual fish. Videos of two separate fish swimming modes were analyzed. The two swimming modes are termed `free-stream swimming' and the `Kármán gait'. Free-stream swimming is how fish swim in a section of water that is free of disturbances, while Kármán gait swimming is how fish swim in the presence of a vortex street. Each swimming mode was paired with two simulation configurations, one that is free of obstructions, and one that contains a vortex street generating D-section cylinder. Data about the efficiency of swimming, power output, and thrust production were calculated during the simulations.
The results showed that the most efficient mode of swimming was the Kármán gait in the presence of a Kármán vortex street. Evidence corroborating this has been found in the literature. The second most efficient means of swimming was found to be free-stream swimming in the absence of obstructions. The other two configurations, which are not observed in experiments, performed very poorly in regard to swimming efficiency.