Understanding Bio-Locomotion for Collective Swimming in a Quiet and Disturbed Media

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Living organisms, such as fish, birds, insects, tend to organize themselves into well-defined patterns while performing collective tasks. The current project seeks to understand the role of the environment on the patterns and modes of swimming that can be observed in schools of fish, including the gaits of locomotion, geometrical organization, and synchronization. When fish swim and interact in a viscous fluid media, they experience the flow-mediated drag forces that affect their efficiency and the energy expenditure. The current project is devoted to a search of specific swimming modes that are best suited for certain tasks, for example, in providing the lowest energy expenditure, or the highest speed of motion, given certain constraints, of a collective swimming unit. The fundamental questions are whether, how and why these modes differ or don't differ depending on the task at hand, and how the disturbances in the fluid media, such as wakes, currents, etc., will affect them. This knowledge will help manage and protect natural fish habitats, and assist in engineering and design of autonomous bio-inspired robotic vehicles for various missions. As a part of an educational and outreach program, an interactive software Virtual Robofish will be developed to demonstrate the principles of pattern formation in fish schools to high-school students.The current project seeks to combine fully-resolved hydrodynamic simulations of flexible swimming bodies that self-propel in a viscous fluid media, with gradient-free optimization procedures, in order to reveal and understand the optimal modes of collective bio-locomotion that optimize certain objective functions. Among the objective functions to be considered are the swimming efficiency, swimming speed, and an acoustic signature of a collective swarm. The optimum patterns found via fully-resolved viscous flow simulations will be compared with a low-order finite-dipole potential flow model in order to understand the importance of morphology, kinematics, inertial and viscous effects, omitted in a low-order model, on dynamics of collective swimming. Both the full Navier-Stokes model and the low-order potential flow model will be enhanced to introduce the effect of flow disturbances, such as vortex wakes, velocity currents, etc. The effect that such disturbances have on the optimized swimming modes will be investigated. The generated knowledge will lead to a greater understanding of the principles of self-organization in biological systems, and to practical advances in design, engineering and control of underwater robotic swarms for national security and health applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.