China Safety Science Journal ›› 2023, Vol. 33 ›› Issue (6): 214-222.doi: 10.16265/j.cnki.issn1003-3033.2023.06.1741

• Occupational health • Previous Articles     Next Articles

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 Online:2023-08-07 Published:2023-12-28

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