Adaptively Sampled Particle Fluids

This project presents geometric feature-size based adaptive sampling algorithms for Lagrangian particle fluids. This adaptive sampling strategy allows using smaller (and thus more) particles in geometrically complex regions, while less particles are used for thick flat fluid volumes. Additionally, a novel distance-based particle surface definition is implemented which hides the particle granularity and allows dynamic resampling near the fluid-air interface. The code is implemented in C++ and should compile on linux. <br/><br/>This project includes the following software/data packages: <br/> <ul> <li> <a href="https://simtk.org/frs?group_id=231#pack_314">ASPF </a> : Source code for the Adaptively Sampled Particle Fluids. This is the initial release (see INSTALL file for compilation information). </li> </ul>

本项研究提出了一种基于几何特征尺寸的自适应采样算法，适用于拉格朗日粒子流体。该自适应采样策略允许多在几何复杂区域使用较小的（因而更多的）粒子，而对于厚实的平坦流体体积则使用较少的粒子。此外，本项目还实施了一种基于距离的粒子表面定义新方法，该方法能够隐藏粒子粒度，并允许在流体-空气界面附近进行动态重采样。代码采用 C++ 编写，且应在 Linux 环境下编译无误。

本项目包含以下软件/数据包：

<ul>
<li><a href="https://simtk.org/frs?group_id=231#pack_314">ASPF</a>：自适应采样粒子流体的源代码。这是首次发布版本（编译信息请参阅 INSTALL 文件）。</li>
</ul>