AMR (Adaptive Mesh Refinement) improves the computational efficiency drastically and makes it possible to set outflow boundaries far from ROI. It is also recognized as a key technique for multi-scale studies and suitable for problems of moving interfaces or boundaries. The major difficulties come from data structure, memory management and interpolation at the resolution difference and dynamic domain partitioning to maintain the computational load and used memory balance. An octree-based AMR framework has been developed for GPU supercomputers. We show several implementations of fluid-structure interaction: dolphin free swimming, violent flag fluttering, tsunami flow with a lot of drift woods, expanding soap bubble, in which AMR is needed essentially.
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