期刊
BIOINSPIRATION & BIOMIMETICS
卷 13, 期 2, 页码 -出版社
IOP PUBLISHING LTD
DOI: 10.1088/1748-3190/aaa787
关键词
sensing; swimming; unsteady flows
资金
- Office of Naval Research (ONR) [N00014-14-1-0421, N00014-17-1-2287]
- Army Research Office (ARO) [W911NF-16-1-0074]
- Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program
Unsteady flows contain information about the objects creating them. Aquatic organisms offer intriguing paradigms for extracting flow information using local sensory measurements. In contrast, classical methods for flow analysis require global knowledge of the flow field. Here, we train neural networks to classify flow patterns using local vorticity measurements. Specifically, we consider vortex wakes behind an oscillating airfoil and we evaluate the accuracy of the network in distinguishing between three wake types, 2S, 2P + 2S and 2P + 4S. The network uncovers the salient features of each wake type.
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