The study was motivated by the fact that explosion inside the subway structure may not only cause direct life loss,but also damage the subway structure and lead to further loss of lives and properties.The propagation ...The study was motivated by the fact that explosion inside the subway structure may not only cause direct life loss,but also damage the subway structure and lead to further loss of lives and properties.The propagation law of explosion wave in the subway station was analyzed and a simplified model of overpressure in the subway station was also proposed.Whereafter,the improved dynamic cam-clay model of soil and the concrete damaged plasticity constitutive model were used for the dynamic analysis of the subway station.Meanwhile,the influences of soil stiffness and burial depth on the dynamic response of the subway station were looked into.The results show that the multi-peak overpressure in the subway station does not appear,and large stresses concentrate on the central column and the floor slab of the subway station,so some special reinforcement measures should be taken in these parts.The effect of soil stiffness and burial depth on the stress of the central column is little;however,the effect on the stress of the station side wall is relatively obvious.展开更多
This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passi...This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passing time acquired and calculated in the waiting area of the prediction escalator to select the gates related to the predicted the escalator. NARX neural network is used to predict the model of the passenger flow parameters of the escalator waiting area based on the related gates＇ AFC data, then a probabilistic neural network model was established by using the AFC data and predicted passenger flow parameters as input and the passenger flow status in the escalator waiting area of subway station as output.The result shows the predicting model can predict the passenger flow status of the escalator waiting area better by the AFC data in the subway station. Research result can provide decision basis for the operation management of the subway station.展开更多
基金Project(50978043) supported by the National Natural Science Foundation of China
文摘The study was motivated by the fact that explosion inside the subway structure may not only cause direct life loss,but also damage the subway structure and lead to further loss of lives and properties.The propagation law of explosion wave in the subway station was analyzed and a simplified model of overpressure in the subway station was also proposed.Whereafter,the improved dynamic cam-clay model of soil and the concrete damaged plasticity constitutive model were used for the dynamic analysis of the subway station.Meanwhile,the influences of soil stiffness and burial depth on the dynamic response of the subway station were looked into.The results show that the multi-peak overpressure in the subway station does not appear,and large stresses concentrate on the central column and the floor slab of the subway station,so some special reinforcement measures should be taken in these parts.The effect of soil stiffness and burial depth on the stress of the central column is little;however,the effect on the stress of the station side wall is relatively obvious.
文摘This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passing time acquired and calculated in the waiting area of the prediction escalator to select the gates related to the predicted the escalator. NARX neural network is used to predict the model of the passenger flow parameters of the escalator waiting area based on the related gates＇ AFC data, then a probabilistic neural network model was established by using the AFC data and predicted passenger flow parameters as input and the passenger flow status in the escalator waiting area of subway station as output.The result shows the predicting model can predict the passenger flow status of the escalator waiting area better by the AFC data in the subway station. Research result can provide decision basis for the operation management of the subway station.
