Abstract

In order to provide theoretical support for high-quality construction of Sichuan-Tibet railway project, the construction risk level of Sichuan-Tibet railway project should be evaluated scientifically and reasonably. This paper analyses the characteristics of bridge and tunnel construction projects in view of the five super-large bridges and nine super-long tunnels in the construction of Sichuan-Tibet railway, constructing seventeen safety risk evaluation index systems for bridge engineering and twenty safety risk evaluation index systems for tunnel engineering, establishing the risk assessment model to complete the risk assessment of key bridges and tunnels of Sichuan-Tibet railway. Finally, the BP neural network model is constructed to validate the results of risk assessment. This BP network model has three layers, the maximum number of training times is 10,000, the hidden layer neurons are 15, the hidden layer activation function is Tansig function, the output layer activation function is logig function, the training function is trainlm function, and the learning function is learngdm function. The training data are scoring data of some key bridges and some key tunnels of Sichuan-Tibet railway, and the remaining scoring results are used as validation data, to predict the risk level of bridge and tunnel engineering. The results show that the accuracy of predicting the safety risk grade of bridge and tunnel engineering by BP neural network is 92.86%. BP neural network is applicable to the risk assessment model. 50% of the key bridge and tunnel projects of Sichuan-Tibet railway are in danger, and only 20% of the projects are in safety grade. Therefore, it is suggested that construction units pay attention to the safety supervision of construction personnel, strict control of the quality of construction equipment and materials. For different possible accidents, relevant units should start emergency plans as soon as possible, take safety protection measures, avoid continuous operation of cold and anoxia as far as possible, minimize the time of frequent geological activities, and further analyze the hidden dangers of construction risks. To reduce or even eliminate risk sources fundamentally.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.