Abstract Industrial fires are undeniably the most dangerous type of fires for firefighters, and the master stream from water monitor is one of the safest means to deploy defensive or offensive strategies against such fires. However, few studies pay attention to the efficacy of the master stream. To address this issue, we extracted and analyzed numerical data from physical master streams. The proposed methods comprising of digital image processing (DIP) and large-scale particle image velocimetry (LS-PIV), which were conducted in the full-scale discharge in order to obtain coordinate trajectory pattern as well as the instantaneous and mean vector-velocity fields. The flow vectors in the different zones of the master stream were compared using KAZE feature detection. This study thus offers more extensive and detailed experimental data to validate computational fluid dynamics (CFD) simulations and opens an avenue for future fire-safety research.

中文翻译：

---

大规模PIV在水监测排放实验中的应用

摘要 工业火灾无疑是消防员面临的最危险的火灾类型，而水炮主流是针对此类火灾部署防御或进攻策略的最安全手段之一。然而，很少有研究关注主码流的功效。为了解决这个问题，我们从物理主流中提取并分析了数值数据。所提出的方法包括数字图像处理（DIP）和大尺度粒子图像测速（LS-PIV），它们在全尺度放电中进行，以获得坐标轨迹模式以及瞬时和平均矢量速度领域。使用 KAZE 特征检测比较了主流不同区域的流向量。