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Methodology for DB construction of input parameters in FDS-based prediction models of smoke detector
Journal of Mechanical Science and Technology ( IF 1.5 ) Pub Date : 2021-01-04 , DOI: 10.1007/s12206-020-1133-0
Hyo-Yeon Jang , Cheol-Hong Hwang

The input parameters of the Heskestad and Cleary models—which are numerical models included in fire dynamics simulator (FDS)—are measured, and a sensitivity analysis is conducted on the effects of individual and common input parameters of the numerical models on the detection time. The input parameters are applied to the FDS, and the results predicted the activation time of the detector within +5 s. Compared to the individual input parameters, the obscuration per meter (OPM), which is a common input parameter, significantly affected the detection time. Finally, additional input parameters that correspond to combustion properties, such as the soot yield and mass specific extinction coefficient, are discovered to have a greater impact on the detection time than the input parameters in the detector’s numerical models. Considering various smoke detectors and combustibles, this study’s findings will contribute to the efficient use of resources to build a database of input parameters.



中文翻译:

基于FDS的烟雾探测器预测模型中输入参数的DB构造方法

测量了火灾动态模拟器(FDS)中包含的数值模型Heskestad和Cleary模型的输入参数,并对数值模型的单个和通用输入参数对检测时间的影响进行了敏感性分析。将输入参数应用于FDS,结果可预测检测器的激活时间在+5 s之内。与单独的输入参数相比,每米的浊度(OPM)是一种常见的输入参数,它显着影响检测时间。最后,与燃烧器数值模型中的输入参数相比,发现与燃烧特性相对应的其他输入参数(如烟yield收率和质量消光系数)对检测时间的影响更大。

更新日期:2021-01-04
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