题 目：以自然为师：仿生推进中的性能增强机制（Learning from Nature: New Body-involved Performance Enhancement Mechanism in Bio-inspired Propulsion）
报 告 人：董海波 副教授 （University of Virginia）
时 间：2018年6月14日（周四）13：30
地 点：延长校区应用数学和力学所东会议室
摘 要：In this talk, a combined experimental and computational approach will be introduced for studying unsteady flow physics of freely flying and swimming animals. High-speed photogrammetry system and an accurate 3D data reconstruction technique are used together to measure the kinematics of animal body and appendages with extraordinary details. A model reduction tool is developed to extract the dominant kinematical components for analysis and computational modeling. A Cartesian-grid-based immersed boundary solver is then used to simulate corresponding unsteady flows in all their complexity. A block-based Adaptive Mesh Refinement (AMR) technique is used to enhance the computational ability and increase the computational efficiency for the application of high-Reynolds number flow and complex geometries. Analysis of vortex dynamics due to body-appendage interactions and associated aero/hydro-performance of insect flight and fish swimming will be discussed. The discovery of the new body-involved performance enhancement will bring new insights on the design of highly efficient bio-inspired robotic systems.
