Abstract
The studies of flow field affected by fish swimming and their three-dimensional (3D) dynamics characteristics are important inspirations and guides for the proper understanding of fish swimming mechanism, the development of bionic fish, and bionic fish propulsion system. The emergence of Dynamic Mode Decomposition (DMD) provides a new research perspective to study the flow mechanism and dynamics characteristics of fish swimming, but the traditional DMD decomposition, reconstruction, and prediction mainly focus on the two-dimensional (2D) characteristics of the flow field data, which cannot fully capture the three-dimensional dynamics characteristics of the flow field. Based on this, this paper adopts the 3D velocity data of the fluid domain generated by simulations with Immersed Boundary-Lattice Boltzmann Method (IB-LBM) to study the swimming mechanism of the bionic fish. The velocity field data are decomposed, reconstructed, and predicted in 3D by DMD. The results showed that two rows of semicircular vortex structures alternately shed and developed on both sides of the fish with obvious 3D characteristics. The frequencies of Mode 2 and Mode 3 obtained from the dynamical mode decomposition are 1.0899, which are consistent with the frequency of the tail undulation. The 3D DMD can reconstruct and predict the main features of the flow field with high accuracy based on few snapshots of the flow field, with a Root Mean Square Error (RMSE) of 3.232 × 10−3 and a Mean Absolute Error (MAE) of 7.096 × 10−4. Compared with the 2D DMD, the 3D DMD decomposition, reconstruction, and prediction can obtain the 3D characteristics of the fish swimming mechanism. It can help to understand and recognize the 3D dynamic behaviors of the fish swimming in a more intuitive and comprehensive way.
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