首页> 外文期刊>Journal of Mechanical Science and Technology >Methodology for DB construction of input parameters in FDS-based prediction models of smoke detector
【24h】

Methodology for DB construction of input parameters in FDS-based prediction models of smoke detector

机译:基于FDS的烟雾检测器预测模型中输入参数的DB施工方法

获取原文
获取原文并翻译 | 示例
       

摘要

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.
机译:测量了火灾动力学模拟器(FDS)中的数值模型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探测时间的影响进行了灵敏度分析。将输入参数应用于FDS,结果预测了探测器在+5 s内的激活时间。与单个输入参数相比,每米模糊度(OPM)是一个常见的输入参数,显著影响了检测时间。最后,与探测器数值模型中的输入参数相比,与燃烧特性相对应的其他输入参数,如烟尘产率和质量比消光系数,对探测时间的影响更大。考虑到各种烟雾探测器和可燃物,本研究的发现将有助于有效利用资源,建立输入参数数据库。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号