Journal Published Online: 11 January 2019
Volume 48, Issue 6

Fire Water Monitor Trajectories Based on Turbulence Breakup Model

CODEN: JTEVAB

Abstract

Fire remains one of the most pervasive threats to public safety and social development in real life. Fire water monitors have been used as tools for ending the fire all the time. The impact point accuracy of the water jet and the accurate prediction of the water jet trajectory have a significant effect on the efficiency of fire extinction. The quadratic drag model is selected on the basis of the analysis of the mechanical model of fluidic control volume considering the change of the cross-sectional area caused by the velocity and breakup of the water jet. The change of diameter and area of the droplet are also discussed, based on the theory of liquid jet breakup, to build a dynamic breakup model of air resistance and broken jet. The water jet simulations are performed on two different scales by researching several main performance parameters, such as discharge angle and initial velocity, which can affect the jet trajectory of fire water monitor. The influences of various parameters on the jet trajectory are summarized through the simulations of two kinds of water jet experimental data, and an accurate prediction of the jet trajectory of fire water monitor is realized.

Author Information

Zhang, Minghui
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, People’s Republic of China
Liu, Xintian
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, People’s Republic of China
Wang, Xiaolan
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, People’s Republic of China
Wang, Yansong
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, People’s Republic of China
Liang, Wei
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, People’s Republic of China
Pages: 19
Price: $25.00
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Details
Stock #: JTE20180428
ISSN: 0090-3973
DOI: 10.1520/JTE20180428