A. Urano*, K. Tajiri1, M. Tanaka, M. Yamakawa & H. Nishida

Department of Mechanophisics, Kyoto Institute of Technology, Hashikami-cho Matsugasaki, Sakyo-Ku, Kyoto 606-8585, Japan

*Corresponding Author Email: [email protected]

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In this study, we constructed the ALE seamless immersed boundary method (ALE SIBM) with the overset grid system using the sub-grid adapted to the shape of an object. In this paper, we discussed the effectiveness of the present method. The ALE SIBM is the combined method of the SIBM and arbitrary Lagrangian-Eulerian (ALE) method to efficiently analyze flow around moving objects on the Cartesian grid. In the ALE SIBM with the overset grid system, the ALE SIBM is applied only to the sub-grid in order to efficiently perform flow analysis including multiple moving objects. Generally, the sub-grid is formed in rectangular area on a Cartesian overset grid. However, depending on the shape of the object, it may form an unnecessary area for flow analysis. Therefore, in this study, in order to reduce unnecessary computational grid points, we constructed the method to reconstruct the sub-grid adapted to the shape of the object. By using the present method, it is possible to compute with the optimal number of the grid points of the sub-grid according to the shape of the object, and the computational cost can be reduced. In this study, ALE-SIBM with the overset grid system adapted to the virtual boundary was applied to the flow including a translating circular cylinder in the channel, and its effectiveness was verified. In order to verify the present method, the results obtained by the present method was compared with the results obtained by the SIBM on the single grid and the conventional ALE-SIBM with the overset grid system non-adapted to the virtual boundary. As a result, the number of computational grid points in the present method was greatly reduced compared to the conventional method. In addition, the results by the present method were in good agreement with the results by other methods quantitatively and qualitatively. Therefore, it was confirmed that the computational accuracy can be maintained while reducing the number of computational grid points by using the present method. In the future, applications to various objects and their verification are desired.