耦合拉格朗日-欧拉方法及其在海洋工程中的应用

Combining the strengths of Lagrangian and Eulerian descriptions,the coupled Lagrangian–Eulerian methods play an increasingly important role in various subjects.This work reviews their development and application in ocean engineering.Initially,we briefly outline the advantages and disadvantages of the Lagrangian and Eulerian descriptions and the main characteristics of the coupled Lagrangian–Eulerian approach.Then,following the developmental trajectory of these methods,the fundamental formulations and the frameworks of various approaches,including the arbitrary Lagrangian–Eulerian finite element method,the particle-in-cell method,the material point method,and the recently developed Lagrangian–Eulerian stabilized collocation method,are detailedly reviewed.In addition,the article reviews the research progress of these methods with applications in ocean hydrodynamics,focusing on free surface flows,numerical wave generation,wave overturning and breaking,interactions between waves and coastal structures,fluid–rigid body interactions,fluid–elastic body interactions,multiphase flow problems and visualization of ocean flows,etc.Furthermore,the latest research advancements in the numerical stability,accuracy,efficiency,and consistency of the coupled Lagrangian–Eulerian particle methods are reviewed;these advancements enable efficient and highly accurate simulation of complicated multiphysics problems in ocean and coastal engineering.By building on these works,the current challenges and future directions of the hybrid Lagrangian–Eulerian particle methods are summarized.

3D large-scale SPH modeling of vehicle wading with GPU acceleration

Vehicle wading is a complex fluid-structure interaction(FSI) problem and has attracted great attention recently from the automotive industry, especially for electric vehicles. As a meshless Lagrangian particle method, smoothed particle hydrodynamics(SPH) is one of the most suitable candidates for simulations of vehicle wading due to its inherent advantages in modeling free surface flows, splash, and moving interfaces. Nevertheless, the inevitable neighbor query for the nearest adjacent particles among the support domain leads to considerable computational cost and thus limits its application in 3D large-scale simulations. In this work, a GPU-based SPH method is developed with an adaptive spatial sort technology for simulations of vehicle wading. In addition, a fast, easy-to-implement particle generator is presented for isotropic initialization of the complex vehicle geometry with optimal interpolation properties. A comparative study of vehicle wading on a puddle between the GPUbased SPH with two pieces of commercial software is used to verify the capability of the GPU-based SPH method in terms of convergence analysis, kinematic characteristics, and computing performance. Finally, different conditions of vehicle speeds, water depths, and puddle widths are tested to investigate the vehicle wading numerically. The results demonstrate that the adaptive spatial sort technology can significantly improve the computing performance of the GPU-based SPH method and meanwhile promotes the GPU-based SPH method to be a competitive tool for the study of 3D large-scale FSI problems including vehicle wading. Some helpful findings of the critical vehicle speed, water depth as well as boundary wall effect are also reported in this work.