A novel level-set-based immersed boundary method for simulating complex 3D fish-like swimming

The immersed boundary method (IBM) has been extensively applied to the modeling and simulation of three-dimensional fish-like swimming. The high Reynolds number, complex body morphology, or large computational domain often cause the immersed boundary reconstruction costly and introduce numerical difficulties during simulations. The level set (LS) method and adaptive mesh refinement (AMR) method partially solved the aforementioned problems, however, the high computational cost for immersed boundaries reconstruction in 3D fish-like swimming is still a problem, especially for a fish with a high Reynolds number and complex geometry, and fish school swimming. For example, even though, with the AMR technique, the computational load of simulation for fish school swimming has been distributed into separate nodes, the immersed boundary reconstruction in the AMR blocks with the finest mesh or the larger AMR blocks encompassing all fish bodies could also greatly increase the computational cost for the simulation. Thus, in this work, a narrow-band level-set-based immersed boundary method (NBLS-IBM) has been developed to improve the efficiency of simulating complex 3D fish-like swimming including shark-like body swimming and fish school swimming. This novel level-set-based immersed boundary method reduces the computational cost for boundary reconstruction from O(n³) to O(kn²).