为了预测鱼类游泳问题的流动演变,开发了一种基于浸入边界格子玻尔兹曼方法的流动求解器.采用基于隐式边界力校正框架的灵活迭代算法降低计算成本和内存.在确定边界节点的速度修正后动量力由简单的直接力公式描述,无需复杂的积分计算.使用所提出的流动求解器,分析了鱼引起的动态失速涡与非定常流动中的传入涡之间的流体动力学相互作用.数值模拟结果揭示了鱼类利用涡流增强自身水动力性能的机制.优越的游泳性能源于“合并涡流”与鱼尾运动之间的相对运动,相互作用由相位差控制.“合并涡”的形成条件成为鱼类利用涡流提高游泳性能的关键因素.进一步讨论了运动主要成分的影响.根据数值模拟结果得出结论,横向平移在推进中起着至关重要的作用,而与旋转和头部运动相结合的身体起伏降低了运动成本.“,”To predict the flow evolution of fish swimming problems,a flow solver based on the immersed boundary lattice Boltzmann method is developed. A flexible iterative algorithm based on the framework of implicit boundary force correction is used to save the computational cost and memory,and the momentum forcing is described by a simple direct force formula without complicated integral calculation when the velocity correction at the boundary node is determined. With the presented flow solver,the hydrodynamic interaction between the fish-induced dynamic stall vortices and the incoming vortices in unsteady flow is analyzed. Numerical simulation results unveil the mechanism of fish exploiting vortices to enhance their own hydrodynamic performances. The superior swimming performances originate from the relative movement between the“merged vortex”and the locomotion of the fishtail,which is controlled by the phase difference. Formation conditions of the“merged vortex”become the key factor for fish to exploit vortices to improve their swimming performance. We further discuss the effect of the principal components of locomotion. From the results,we conclude that lateral translation plays a crucial role in propulsion while body undulation in tandem with rotation and head motion reduce the locomotor cost.