Session: 01-01-04 Fluid Machinery Symposium

Paper Number: 131405

131405 - Hydrodynamic Interactions in Fish-Like Robotic Swarms With Flexible Propulsors 

An emerging interest for engineers is the study of performance enhancement that swarms of swimmers could achieve. In the biological world, fish schooling is prevalent across a range of species with different bodies, sizes, etc. In the engineering world, replicating this organized swarming has proven difficult. In this study, we will examine the hydrodynamic performance of Bluebots in schooling arrangements. Bluebots are fish-like robots that utilize visual sensing to understand the surroundings and have successfully adopted schooling patterns. Despite this, the hydrodynamic interactions in these Bluebot schools are relatively unknown. Even further, much remains to be understood about how these swarms may take advantage of flow sensing to improve hydrodynamic performance.   

At the core of this study is a 3D Bluebot reconstruction whose motion is determined by model skeletal joints at various points within the body. These joints are prescribed translations and rotations to give the virtual model realistic motion, particularly in the caudal fin (CF) where spatial variation of joint rotations allows for flexibility in the CF to be introduced. To solve the flow field of the cases, we use an immersed boundary method-based incompressible flow solver. In this solver, the 3-D Navier-Stokes equations are discretized using a cell-centered, collocated arrangement of the primitive variables and are solved using a finite difference-based Cartesian grid immersed boundary method. The numerical procedures maintain 2^nd order accuracy in both space and time. This direct numerical solver allows us to resolve in detail the near and far wake structures produced by the Bluebot which is important for analyzing the interaction between the two subjects. For each of the cases, the Reynolds number is fixed at 1000 to conserve computational costs. To model the flow sensors on the real Bluebot, we also implement a virtual flow sensor technology that allows us to analyze the flow signals present at sensor locations on the body. This tool draws similarities to the lateral line systems in real fish.

From these simulations, we expect to observe changes in the Bluebot performance through variation of the spatial position and flapping phase. This is of course important to understand from a fundamental fluid physics perspective, however, sensor information is of utmost value to the Bluebot as well. By examining the virtual sensor information, we will also understand how sensor information could have any performance indications. 

Presenting Author: Alec Menzer University of Virginia