时间混合层的原位特征跟踪与可视化

E. Duque, Daniel E. Hiepler, S. Legensky, C. Stone
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引用次数: 1

摘要

通过大涡模拟方法LESLIE3D求解Navier-Stokes方程,分析时间混合层的流场,然后利用原型可视化和CFD数据分析软件系统湍流模拟智能原位特征检测、跟踪和可视化(IFDT)对得到的流场特征进行可视化和后处理。该系统利用具有智能自适应传递函数的体积渲染,允许用户训练可视化系统来突出显示湍流漩涡等流动特征。然后,基于预测-校正方法的特征提取器跟踪和提取流特征并确定特征随时间的统计量。该方法通过Python接口框架与流求解器一起原位执行,以避免将数据保存到文件的开销。为这个可视化展示提交的电影突出了流动的可视化,如漩涡特征的形成,漩涡破裂,湍流的开始,然后是完全混合的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In-Situ Feature Tracking and Visualization of a Temporal Mixing Layer
The flow field for a temporal mixing layer was analyzed by solving the Navier-Stokes equations via a Large Eddy Simulation method, LESLIE3D, and then visualizing and post-processing the resulting flow features by utilizing the prototype visualization and CFD data analysis software system Intelligent In-Situ Feature Detection, Tracking and Visualization for Turbulent Flow Simulations (IFDT). The system utilizes volume rendering with an Intelligent Adaptive Transfer Function that allows the user to train the visualization system to highlight flow features such as turbulent vortices. A feature extractor based upon a Prediction-Correction method then tracks and extracts the flow features and determines the statistics of features over time. The method executes In-Situ with the flow solver via a Python Interface Framework to avoid the overhead of saving data to file. The movie submitted for this visualization showcase highlights the visualization of the flow such as the formation of vortex features, vortex breakdown, the onset of turbulence and then fully mixed conditions.
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