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Bio-inspired flow sensing and Prediction for Fish-like Undulating Locomotion： A CFD-aided Approach

Journal of Bionic Engineering 2015年第3期12卷 406-417页

作者： Han Zhou Tianjiang Hu Kin Huat Low Lincheng Shen Zhaowei Ma Guangming Wang Haijun Xu College of Mechatronics and Automation National University of Defense Technology Changsha 410073 China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha 410073 China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore 639798

Feedback flow information is of significance to enable underwater locomotion controllers with higher adaptability and efficiency within varying environments. Inspired from fish sensing their external flow via near-body pressure, a computational scheme is proposed and developed in this paper. In conjunction with the scheme, Computational Fluid Dynamics （CFD） is employed to study the bio-inspired fish swimming hydrodynamics. The spatial distribution and temporal variation of the near-body pressure of fish are studied over the whole computational domain. Furthermore, a filtering algorithm is designed and implemented to fuse near-body pressure of one or multiple points for the estimation on the external flow. The simulation results demonstrate that the proposed computational scheme and its corresponding algorithm are both effective to predict the inlet flow velocity by using near-body pressure at distributed spatial points.

关键词： bio-inspired fish undulating locomotion flow sensing near-body pressure flow velocity estimation Computational Fluid Dynamics (CFD)

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An artificial lateral line system using IPMC sensor arrays

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International Journal of Smart and Nano Materials 2012年第3期3卷 226-242页

作者： Ahmad T.Abdulsadda Xiaobo Tan Smart Microsystems Laboratory Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMI 48824 USA January 92012

Most fish and aquatic amphibians use the lateral line system,consisting of arrays of hair-like neuromasts,as an important sensory organ for prey/predator detection,communication,and *** this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer-metal composites(IPMCs).Analogous to its biological counterpart,the IPMC-based lateral line processes the sensor signals through a neural *** effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source(vibrating sphere)*** particular,as a proof of concept,a prototype with body length(BL)of 10 cm,comprising six millimeter-scale IPMC sensors,is constructed and *** results have shown that the IPMC-based lateral line can localize the source from 1-2 BLs away,with a maximum localization error of 0.3 cm,when the data for training the neural network are collected from a grid of 2 cm by 2 cm *** effect of the number of sensors on the localization accuracy has also been examined.

关键词： ionic polymer-metal composite(IPMC) lateral line system neural networks flow sensing dipole source localization

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Classifying wakes produced by self-propelled fish-like swimmers using neural networks

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Theoretical & Applied Mechanics Letters 2020年第3期10卷 149-154页

作者： Binglin Li Xiang Zhang Xing Zhang State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100049China

We consider the classification of wake structures produced by self-propelled fish-like swimmers based on local measurements of flow *** problem is inspired by the extraordinary capability of animal swimmers in perceiving their hydrodynamic environments under dark *** train different neural networks to classify wake structures by using the streamwise velocity component,the crosswise velocity component,the vorticity and the combination of three flow variables,*** is found that the neural networks trained using the two velocity components perform well in identifying the wake types,whereas the neural network trained using the vorticity suffers from a high rate of *** the neural network is trained using the combination of all three flow variables,a remarkably high accuracy in wake classification can be *** results of this study can be helpful to the design of flow sensory systems in robotic underwater vehicles.

关键词： flow sensing Machine learning Wake classification Self-propelled swimming Fluid-structure interaction

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