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Background-oriented schlieren technique for two-dimensional visualization of convective indoor air flows
Optics and Lasers in Engineering ( IF 4.6 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.optlaseng.2020.106282
Lia Becher , Conrad Voelker , Volker Rodehorst , Michael Kuhne

Abstract This article focuses on further developments of the background-oriented schlieren (BOS) technique to visualize convective indoor air flow, which is usually defined by very small density gradients. Since the light rays deflect when passing through fluids with different densities, BOS can detect the resulting refractive index gradients as integration along a line of sight. In this paper, the BOS technique is used to yield a two-dimensional visualization of small density gradients. The novelty of the described method is the implementation of a highly sensitive BOS setup to visualize the ascending thermal plume from a heated thermal manikin with temperature differences of minimum 1 K. To guarantee steady boundary conditions, the thermal manikin was seated in a climate laboratory. For the experimental investigations, a high-resolution DLSR camera was used capturing a large field of view with sufficient detail accuracy. Several parameters such as various backgrounds, focal lengths, room air temperatures, and distances between the object of investigation, camera, and structured background were tested to find the most suitable parameters to visualize convective indoor air flow. Besides these measurements, this paper presents the analyzing method using cross-correlation algorithms and finally the results of visualizing the convective indoor air flow with BOS. The highly sensitive BOS setup presented in this article complements the commonly used invasive methods that highly influence weak air flows.

中文翻译:

用于对流室内气流二维可视化的面向背景的纹影技术

摘要 本文重点介绍背景导向纹影 (BOS) 技术的进一步发展,以可视化对流室内空气流,这通常由非常小的密度梯度定义。由于光线在穿过不同密度的流体时会发生偏转,因此 BOS 可以将由此产生的折射率梯度检测为沿视线的积分。在本文中,BOS 技术用于生成小密度梯度的二维可视化。所描述方法的新颖之处在于实施了高度敏感的 BOS 设置,以可视化来自加热热人体模型的上升热羽流,温差最小为 1 K。为了保证稳定的边界条件,热人体模型位于气候实验室中。对于实验研究,使用高分辨率 DLSR 相机以足够的细节精度捕捉大视野。测试了多个参数,例如各种背景、焦距、室温以及调查对象、相机和结构化背景之间的距离,以找到最合适的参数来可视化对流室内空气流。除了这些测量值之外,本文还介绍了使用互相关算法的分析方法,以及使用 BOS 可视化室内对流气流的结果。本文中介绍的高度敏感的 BOS 设置补充了高度影响弱气流的常用侵入性方法。并测试了调查对象、相机和结构化背景之间的距离,以找到最合适的参数来可视化对流室内空气流。除了这些测量值之外,本文还介绍了使用互相关算法的分析方法,以及使用 BOS 可视化室内对流气流的结果。本文中介绍的高度敏感的 BOS 设置补充了高度影响弱气流的常用侵入性方法。并测试了调查对象、相机和结构化背景之间的距离,以找到最合适的参数来可视化对流室内空气流。除了这些测量值之外,本文还介绍了使用互相关算法的分析方法,以及使用 BOS 可视化室内对流气流的结果。本文中介绍的高度敏感的 BOS 设置补充了高度影响弱气流的常用侵入性方法。
更新日期:2020-11-01
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