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A particle system for interactive visualization of 3D flows

机译:用于3D流交互式可视化的粒子系统

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We present a particle system for interactive visualization of steady 3D flow fields on uniform grids. For the amount of particles we target, particle integration needs to be accelerated and the transfer of these sets for rendering must be avoided. To fulfill these requirements, we exploit features of recent graphics accelerators to advect particles in the graphics processing unit (GPU), saving particle positions in graphics memory, and then sending these positions through the GPU again to obtain images in the frame buffer. This approach allows for interactive streaming and rendering of millions of particles and it enables virtual exploration of high resolution fields in a way similar to real-world experiments. The ability to display the dynamics of large particle sets using visualization options like shaded points or oriented texture splats provides an effective means for visual flow analysis that is far beyond existing solutions. For each particle, flow quantities like vorticity magnitude and A2 are computed and displayed. Built upon a previously published GPU implementation of a sorting network, visibility sorting of transparent particles is implemented. To provide additional visual cues, the GPU constructs and displays visualization geometry like particle lines and stream ribbons.
机译:我们提出了一个粒子系统,用于在统一网格上对稳定的3D流场进行交互式可视化。对于我们目标的粒子数量,需要加速粒子集成,并且必须避免为了渲染而转移这些集合。为了满足这些要求,我们利用最新的图形加速器的功能来平整图形处理单元(GPU)中的粒子,将粒子位置保存在图形内存中,然后再次通过GPU发送这些位置以获取帧缓冲区中的图像。这种方法可以进行交互式流传输和数百万个粒子的渲染,并且可以以类似于实际实验的方式对高分辨率场进行虚拟探索。使用诸如阴影点或定向纹理图示的可视化选项显示大粒子集动力学的能力为视觉流分析提供了有效的手段,这远远超出了现有解决方案。对于每个粒子,将计算并显示诸如涡度大小和A2之类的流量。基于先前发布的排序网络的GPU实现,对透明粒子进行可见性排序。为了提供其他视觉提示,GPU构造并显示可视化几何图形,例如粒子线和流带​​。

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