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作 者:鲁大营 LU Da-ying(College of Software,Qufu Normal University,Qufu 273165,China)
出 处:《软件导刊》2022年第12期162-167,共6页Software Guide
基 金:国家自然科学基金项目(61532002,61601261);山东省高等学校科技计划项目(J17KA062);教育部产学合作协同育人项目(201602028014);山东省研究生教育质量提升计划项目(SDYKC19183);曲阜师范大学大学生创新创业训练计划项目(2017A221)。
摘 要:传统空气污染浓度可视化方法无法显示完整的视觉结果,且容易导致可视化感知问题,如出现遮挡或杂乱无章甚至伪像等。针对上述问题提出一种高效的可视化方法,基于图形硬件的可编程性,统计分析大气风场区域特性进行种子点预采样,通过四面体点定位算法快速构建场线,结合箭头跟踪和等值面绘制与分析污染物的可扩散运动。同时利用聚类算法实现场线抽取,设计光照模型以减少场线与等值面之间的相互遮挡,有效解决了三维流场中出现的感知问题,呈现出清晰的流场模式、空气污染物浓度分布及区域性变化,大大提高了空气污染物浓度数据的可读性。Traditional air pollution concentration visualization methods cannot display complete visual results, and easily lead to visual perception problems, such as occlusion or chaos or even artifacts. In view of the above problems, an efficient visualization method is proposed.Based on the programmability of graphics hardware, the regional characteristics of atmospheric wind field are statistically analyzed, seed points are pre sampled, field lines are quickly constructed through tetrahedral point positioning algorithm, and the diffusible movement of pollutants is analyzed by combining arrow tracking and iso-surface rendering. At the same time, field line extraction is realized by clustering algorithm, and lighting model is designed to reduce the mutual occlusion between streamline and iso-surface, which effectively solved the perception problems in the three-dimensional flow field, shows a clear flow field mode, air pollutant concentration distribution and regional changes, and greatly improves the readability of air pollutant concentration data.
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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