Risk analysis of deep foundation pit construction in adjacent underpass tunnels based on dynamic Bayesian network
In order to reduce the construction risk and disaster loss of deep foundation pits in adjacent existing underpass tunnels and scientifically prevent construction safety accidents,a deep foundation pit construction risk analysis model based on dynamic Bayesian network(DBN)was proposed.Firstly,the BWM(best worst method)was applied to determine the weights of the criteria.Secondly,the interrelationships between risk factors were mined based on association rules,and the dynamic Bayesian network structure model was constructed in this way.Finally,the effectiveness and applicability of the proposed method were examined by taking the deep foundation pit project of the underground layer of the social corridor of the new Xiamen North Station as an example.The results show that the probability of the safety of the pit enclosure being rated as"high"and"very high"in the static state is 34.6%and 36.1%,respectively,and this result changes dynamically with the input risk evidence,and the risk of water seepage of the enclosure piles can be identified quickly by using reverse reasoning.The proposed model can clarify the key risk points in the risk transfer process of deep foundation pit construction in adjacent existing underpass tunnels,and can make dynamic risk prediction and post-accident causation diagnosis of the risk,so as to realize the dynamic control of the construction risk of foundation pit construction in adjacent existing underpass tunnels.The proposed optimized dynamic Bayesian network model has good applicability and high accuracy for pre-construction risk assessment,a priori analysis and risk diagnosis,which can provide effective decision support for safety control during the construction of deep foundation pits of adjacent existing tunnels,and greatly improve the efficiency of risk control.
foundation engineeringdynamic risk assessmentBWM(best worst method)deep foundation pitdynamic Bayesian networkassociation rule mining
万方数据
维普
