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李观, 单桂华, 高阳, 刘俊. 四面体网格化的粒子数据特征可视化[J]. 计算机辅助设计与图形学学报, 2017, 29(1): 1-7.
引用本文: 李观, 单桂华, 高阳, 刘俊. 四面体网格化的粒子数据特征可视化[J]. 计算机辅助设计与图形学学报, 2017, 29(1): 1-7.
Li Guan, Shan Guihua, Gao Yang, Liu Jun. Feature Visualization of Particle Data with Tetrahedral Mesh[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(1): 1-7.
Citation: Li Guan, Shan Guihua, Gao Yang, Liu Jun. Feature Visualization of Particle Data with Tetrahedral Mesh[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(1): 1-7.

四面体网格化的粒子数据特征可视化

Feature Visualization of Particle Data with Tetrahedral Mesh

  • 摘要: 天文粒子数据的可视化对科学家研究宇宙的结构和演化的过程有非常大的帮助,特别是借助于时序可视化可以表现复杂的结构特征,是其他方法无法达到的.文中分析了现有的粒子绘制方式,提出了一种优化的四面体网格粒子绘制算法.算法在数据处理阶段,按粒子编号切分成N个数据片,同时计算不同时刻同一粒子运动状态标记量;在组建四面体阶段,根据周期性边界条件和粒子的运动状态,将粒子数据组成四面体网格;保持不同时刻四面体的组成粒子不变,然后对这些四面体进行投影和绘制.文中算法内存占用小并且适合并行化处理.通过实验,将可视化结果与粒子投影的绘制算法对比,证明文中算法在展现宇宙的结构特征上有很大的优势,并且使宇宙的纤维结构更加连贯完整.

     

    Abstract: Visualization of astronomical particle data could greatly help the scientists to understand the structure and evolution of the universe. Temporal data visualization can show complex structural features in the process of simulation, which can't be achieved by other methods. In this paper, we analyze the existing particle rendering methods, and propose an optimal method based on the tetrahedral mesh. In the data processing stage of the optimal method, we divided the particles to N slices according to the particle ID, and at the same time, we calculate the movement state of the same particle at different times. On the stage of constructing tetrahedral, we use the particle data to construct tetrahedron and use the tetrahedron to construct mesh according to the periodic boundary condition and the particle's motion state. Then we employ the tetrahedral mesh to project and rendering, keeping the particles which construct tetrahedron unchanged at different times. This algorithm consumes less memory than the original one and it suits for parallel computing. We compare the visualization results generated by our algorithm with the particle projection algorithm. The new algorithm has a great advantage in showing the structure of the universe, and it can make the filament more coherent and complete.

     

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