Fire Risk Assessment Using the Building Fire Safety Engineering Method

1996 ◽  
Vol 8 (4) ◽  
pp. 157-167 ◽  
Author(s):  
C. Wade ◽  
P. Whiting
Keyword(s):  
Risk Assessment ◽  
Fire Safety ◽  
Fire Risk ◽  
Engineering Method ◽  
Safety Engineering ◽  
Building Fire ◽  
Fire Safety Engineering ◽  
Fire Risk Assessment

scholarly journals An Integrated Method for Fire Risk Assessment in Residential Buildings

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hongfu Mi ◽  
Yaling Liu ◽  
Wenhe Wang ◽  
Guoqing Xiao
Keyword(s):  
Risk Assessment ◽  
Residential Buildings ◽  
Residential Building ◽  
Fire Risk ◽  
Assessment System ◽  
Risk Level ◽  
Mathematical Framework ◽  
Building Fires ◽  
Building Fire ◽  
Fire Risk Assessment

Building fires are characterized by high uncertainty, so their fire risk assessment is a very challenging task. Many indexes and parameters related to building fires are ambiguous and uncertain; as a result, a flexible and robust method is needed to process quantitative or qualitative data and update existing information when new data are available. This paper presents a novel model to deal with the uncertainty of the residential building fire risk and systematically optimize its performance effectiveness. The model includes fuzzy theory, evidence reasoning theory, and expected utility methods. Fuzzy analysis hierarchy process is applied to analyze the residential building fire risk index system and determine the weights of the risk indexes, while the evidence reasoning operator is used to synthesize them. Three buildings were selected as a case study to illustrate the proposed fire risk model. The results show that the fire risk level of three buildings corresponds to “moderate” or below which is consistent with the previous study. These results also truly reflect the actual situation of fire safety in these residential buildings. The application of this model provides a powerful mathematical framework for cooperative modeling of the fire risk assessment system and allows data to be analyzed step by step in a systematic manner. It is expected that the proposed model could provide managers and researchers with flexible and transparent tools to effectively reduce the fire risk in the system.

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