J4 ›› 2015, Vol. 12 ›› Issue (3): 406-417.doi: 10.1016/S1672-6529(14)60132-3
Bio-inspired Flow Sensing and Prediction for Fish-like Undulating Locomotion: A CFD-aided Approach
Han Zhou1, Tianjiang Hu1,2, Kin Huat Low3, Lincheng Shen1| Zhaowei Ma1, Guangming Wang1, Haijun Xu1
- 1. College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China
2. State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha 410073, China
3. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798
Bio-inspired Flow Sensing and Prediction for Fish-like Undulating Locomotion: A CFD-aided Approach
Han Zhou1, Tianjiang Hu1,2, Kin Huat Low3, Lincheng Shen1| Zhaowei Ma1, Guangming Wang1, Haijun Xu1
- 1. College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China
2. State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha 410073, China
3. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798
摘要：
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.