An Adaptive Boundary Material Point Method With Surface Particle Reconstruction

The expression of fine details such as fluid flowing through narrow pipes or split by thin plates poses a significant challenge in simulations involving complex boundary conditions. As a hybrid method, the material point method (MPM), which is widely used for simulating various materials, combines the advantages of Lagrangian particles and Eulerian grids. To achieve accurate simulations of fluid flow through narrow pipes, high-resolution uniform grid cells are necessary, but this often leads to inefficient simulation performance. In this article, we present an adaptive boundary material point method that facilitates adaptive subdivision within regions of interest and conducts collision detection across grids of varying sizes. Within this framework, particles interact through grids of differing resolutions. To tackle the challenge of unevenly distributed subdivided particles, we propose a surface reconstruction approach grounded in the color distance field (CDF), which accurately defines the relationship between the particles and the reconstructed surface. Furthermore, we incorporate a mesh refinement technique to enrich the detail of the mesh utilized to mark the grids during subdivision. We demonstrate the effectiveness of our approach in simulating various materials and boundary conditions, and contrast it with existing methods, underscoring its distinctive advantages.

Duke Scholars

Author Feng Tian DKU Faculty