| In recent years,a large number of construction safety accidents have caused significant losses to the lives and property of the vast population in China,seriously endangering social stability in China.With the introduction of the national policy of "safety first,prevention first,and comprehensive governance",governments at all levels have responded positively and continuously increased the intensity of relevant supervision and management.Safety production management has gradually become one of the important factors affecting the development of various construction enterprises.In highway construction,the safety management of highway construction has always been an urgent problem to be solved,which will help improve our construction management level.From the perspective of case study,this study,based on the analysis of previous safety production accident texts,combined with interviews with project management personnel of J Expressway and consulting project construction materials,used Bayesian network analysis methods to build the safety production risk assessment model of J Expressway project,and used project risk management knowledge to design the safety production management and control strategies and measures of the project.The main research work of the paper includes the following content:(1)A set of safety risk factors is constructed and analyzed in detail,and then a safety risk checklist is designed.The safety risk factors of the project construction are summarized through the literature analysis method,and the safety risk checklist is designed.The safety risk factors of the project are identified and classified by using the interview method and consulting the construction data of the J expressway project,compared with the safety risk checklist,so that the safety risk factors of the J expressway project can be understood more quickly,and finally the safety risk factors of the J expressway project can be obtained.(2)The prior probability of each safety risk factor is obtained by combining expert experience and knowledge with triangular fuzzy number.Invite experts to evaluate and score various safety risk factors,introduce fuzzy language variables into the evaluation of experts,and use triangular fuzzy numbers to solve them,and finally obtain a priori probability.The conditional probability of safety risk factors is obtained by using content analysis method.The calculation data source of conditional probability parameters is various engineering safety accidents that have occurred.The content analysis method is used to analyze the collected construction safety accidents that have occurred.On this basis,the weight ratio method is used to quantify the data processed by the content analysis method to further determine the conditional probability.This paper proposes a safety risk model of J expressway project based on Bayesian network.Based on the discussion with experts and the analysis of the Provisional Regulations on the Investigation and Treatment of Hidden Danger of Safety Production Accidents,and combining with previous examples,the paper analyzes and determines the relationship between the safety risk factors of J expressway project,and establishes the Bayesian network model of safety risk of J expressway project by combining the prior probability of the root node and the conditional probability of each factor node,Use Bayes Netica 5.18 software to build Bayes network of risk factors and study the parameters of Bayes network model.The Bayesian inverse function is used to obtain the posterior probability of nodes,and the key safety risk factors that cause accidents can be intuitively obtained.(3)The safety management strategies and measures for J expressway project are formulated.This paper introduces the safety management methods of construction projects,the types and contents of safety management inspection and supervision,and how to deal with the safety risks of construction projects,and develops management measures and emergency plans for safety accidents in view of the unsafe factors of human,material and organization management in J expressway project. |