摘要
An adaptive version of immersed boundary method for simulating flows with complex stationary and moving boundaries is presented.The method employs a ghost-cell methodology which allows for a sharp representation of the immersed boundary.To simplify the implementation of the methodology,a volume-of-fluid method is introduced to identify the immersed boundary.In addition,the domain is spatially discretized using a tree-based discretization which is relatively simple to implement a fully flexible adaptive refinement strategy.Finally,the methodology is validated by comparing it with numerical and experimental results on three cases:(1) the flow passing a circular cylinder at Re=40 and Re=100,(2) a periodic oscillation of a circular cylinder in fluid at rest and(3) the self-propelled fish-like swimming at Re=6400.
An adaptive version of immersed boundary method for simulating flows with complex stationary and moving boundaries is presented.The method employs a ghost-cell methodology which allows for a sharp representation of the immersed boundary.To simplify the implementation of the methodology,a volume-of-fluid method is introduced to identify the immersed boundary.In addition,the domain is spatially discretized using a tree-based discretization which is relatively simple to implement a fully flexible adaptive refinement strategy.Finally,the methodology is validated by comparing it with numerical and experimental results on three cases:(1) the flow passing a circular cylinder at Re=40 and Re=100,(2) a periodic oscillation of a circular cylinder in fluid at rest and(3) the self-propelled fish-like swimming at Re=6400.
作者
WANG Liang1 & WU ChuiJie2,3 1 School of Science,PLA University of Science and Technology,Nanjing 211101,China
2 State Key Laboratory of Structural Analysis for Industrial Equipment,Dalian University of Technology,Dalian 116024,China
3 School of Aeronautics and Astronautics,Dalian University of Technology,Dalian 116024,China
基金
supported by the National Natural Science Foundation of China (Grant No. 10672183)
the Prior Research Foundation of PLA University of Science and Technology (Grant No. 2009QX13)
