The free-surface motions interacting with structures are investigated using the Moving Particle Semi-implicit (MPS) method, which was proposed by Koshizuka et al. (1996) for incompressible flow. In the method, Lagrangian moving particles are used for solving flow field instead of Eulerian approach using grid system. Therefore the terms of time derivatives in Navier-Stokes equation can be directly calculated without any numerical diffusion or instabilities due to the fully Lagrangian treatment of fluid particles and topological failure never occur. The MPS method is applied to the numerical study on the impact loads for incompressible flows, such as wet-drop tests and sloshing motions in a LNG tank.

INTRODUCTION

The accurate prediction of impact loads by fluid gives important information for safety of ships or maritime structures. The large deformation and dynamic behavior of free surface are one of the most difficult problems for numerical simulations because the numerical implementation of the fully nonlinear free-surface condition is in general complicated and difficult. There are several techniques to handle such kinds of problems, i.e. SOLA-VOF (Hirt and Nichols, 1981), Level-Set (Sussman et al., 1994), Marker-Density function (MDF) (Miyata and Park, 1995) etc.. Most of them are the techniques capturing the free-surface on grid system. However, there is a different approach using no-grid system, so-called particle methods by use of moving particles with the Lagrangian treatment. The particle methods seem to be more feasible and effective than conventional grid methods for solving the flow field with complicated boundary shapes or the coupling effects between fluid and structure. In the present study, the free-surface motions interacting with structures are investigated using the Moving Particle Semi-implicit (MPS) method, which was proposed by Koshizuka et al. (1996) for incompressible flow. In the method, Lagrangian moving particles are used for solving flow field instead of Eulerian approach using grid system.

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