中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (6): 214-222.doi: 10.16265/j.cnki.issn1003-3033.2023.06.1741

• 职业卫生 • 上一篇    下一篇

灭火防护服贝叶斯建模与热防护性能影响分析

刘纪坤(), 马传丽, 杨杰   

  1. 西安科技大学 安全科学与工程学院,陕西 西安 710054
  • 收稿日期:2023-01-12 修回日期:2023-04-10 出版日期:2023-08-07
  • 作者简介:

    刘纪坤 (1982—),男,河南清丰人,博士,副教授,主要从事风险控制与应急管理方面的研究。E-mail:

  • 基金资助:
    国家自然科学基金资助(51904228)

Bayesian-inference-based fire protective clothing model and thermal protective performance impact analysis

LIU Jikun(), MA Chuanli, YANG Jie   

  1. College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an Shaanxi 710054, China
  • Received:2023-01-12 Revised:2023-04-10 Published:2023-08-07

摘要:

为揭示灭火防护服传热参数对热防护性能的作用机制,结合贝叶斯推断,构造灭火防护服传热参数与热防护性能指标的概率回归关系。基于表征灭火防护服“环境-服装-空气层-皮肤”传热过程的时变微分方程组,提取影响热防护性能的传热参数;利用贝叶斯推断方法,构造织物传热参数与热防护性能指标的概率回归模型,分析传热参数对热防护性能影响的权重大小以及概率分布信息,并进一步借助交叉检验验证所提贝叶斯模型的有效性。结果表明:显热容、织物厚度与烧伤时间近似呈正相关关系,热传导率与烧伤时间近似呈负相关关系;此外,织物厚度对热防护性能的影响显著大于显热容以及热传导率。该模型能反映不同织物参数对皮肤烧伤指标的影响程度,实现织物参数对热防护性能影响的有效量化评价。

关键词: 灭火防护服, 贝叶斯推断, 热防护性能, 传热模型, 烧伤时间

Abstract:

To depict the influence mechanism of heat transfer parameters on the thermal protection performance, the probabilistic regression relation between multi-heat transfer parameters and thermal protection performance index of fire-fighting protective clothing was constructed using Bayesian inference. Combined with the time-varying differential equation concerning the heat transfer process of "environment-clothing-air layer-skin", several characteristic heat transfer parameters affecting the thermal protection performance were extracted. On this basis, a Bayesian inference-based probabilistic regression model was constructed, and the weight and probability distribution information of the influence of heat transfer parameters on thermal protection performance were analyzed. Furthermore, the feasibility of the constructed model was demonstrated within a cross-validation analysis. The results suggest that there is a positive correlation between the apparent heat capacity, the fabric thickness and the burn time, while there is a negative correlation between thermal conductivity and burn time. The influence of the fabric thickness on the thermal protection performance is greater than sensible heat capacity and thermal conductivity. In addition, the impact of different fabric parameter setting on skin burn index via this proposed model can be approximately quantified.

Key words: fire protective clothing, Bayesian inference, thermal protection performance, heat transfer model, burn time