Fish and birds use complex high-speed maneuvers when chasing prey or escaping predators. How water and air flow around these animals during maneuvers is mostly unknown. Mapping out these flows will help biologists better understand the relationship between fish, birds, and their environment. Mapping out these flows will help bio-inspired roboticists, who currently rely on models of low-speed, symmetric gaits when designing and testing robots. Understanding the flows that govern rapid maneuvers will enable a new generation of fast, flexible, ultra-maneuverable bio-inspired robots. The principal goal of this project is therefore to discover the fluid dynamics that govern high-speed, asymmetric swimming/flying gaits. The project integrates educational activities, including virtual tours where students from rural high schools teleconference into the lab and remotely control a robotic swimming rig.
This project is made possible by a unique rig that creates high-frequency, asymmetric flapping motions in a water channel. The rig uses a scotch-yoke mechanism to double the frequencies traditionally available to studies of swimming and flying, and it floats on air bushings in order to simulate autonomous maneuvers. The performance of fish- and bird-inspired propulsion strategies are then quantified by a combination of Particle Image Velocimetry and dynamic force measurements. These experiments will inform adaptations to models of unsteady aerodynamics as they pertain to swimming and flying animals and robots. The experimental-theoretical campaign will focus on three specific research goals: (i) Determine what three-dimensional flow features govern the thrust and efficiency of high-frequency bio-inspired gaits, (ii) Determine what three-dimensional flow features govern the maneuverability of asymmetric bio-inspired gaits, and (iii) Determine what wake-driven models predict the performance of high-frequency, asymmetric, tunable-stiffness fins and wings. More generally, the project's overarching goal is for the unique semiautonomous rig and the associated modeling to create new precedents and templates for those integrating fluid dynamics into the next generation of intelligent machines.