基于粒子系统的时变风场时空动态可视化方法

Lele Chu, Bo Ai, Yubo Wen, Qingtong Shi, Huadong Ma, Wenjun Feng
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引用次数: 1

摘要

粒子系统由于其动力学和仿真特性,在矢量场特征可视化中得到了广泛的应用。然而,基于欧拉场的矢量场可视化方法存在特征表达不清、时间表达不连续等缺陷,无法在时间尺度上有效表达风场特征。为了解决这些问题,我们提出了一种基于时空插值的拉格朗日可视化方法,实现了基于WebGL着色器的粒子系统与时变风数据的融合与表达。首先,根据相邻时刻的风场数据,采用线性插值算法进行插值,得到连续密集的风场数据;然后,我们引入拉格朗日分析方法来研究风场结构,并基于龙格-库塔算法优化粒子系统的可视化效果。最后,采用双标准差(2SD)非线性颜色映射方法,提高风场特征的表达效果。实验结果表明,风的可视化效果较好,渲染帧率大于45帧。该方法在表达连续的风场时空动态可视化特征时,能够使粒子呈现平滑、稳定、均匀性突出。
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A Spatio-Temporal Dynamic Visualization Method of Time-Varying Wind Fields Based on Particle System
The particle system is widely used in vector field feature visualization due to its dynamics and simulation. However, there are some defects of the vector field visualization method based on the Euler fields, such as unclear feature expression and discontinuous temporal expression, so the method cannot effectively express the characteristics of wind field on the temporal scale. We propose a Lagrangian visualization method based on spatio-temporal interpolation to solve these problems, which realizes the fusion and expression of the particle system and the time-varying wind data based on the WebGL shader. Firstly, the linear interpolation algorithm is used to interpolate to obtain continuous and dense wind field data according to the wind field data at adjacent moments. Then, we introduce the Lagrangian analysis method to study the structure of the wind field and optimize the visualization effect of the particle system based on Runge–Kutta algorithms. Finally, we adopt the nonlinear color mapping method with double standard deviation (2SD) to improve the expression effect of wind field features. The experimental results indicate that the wind visualization achieves a comprehensive visual effect and the rendering frame rate is greater than 45. The methods can render the particles smoothly with stable and outstanding uniformity when expressing continuous spatio-temporal dynamic visualization characteristics of the wind field.
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