%0 Journal Article
%A HE Hua-gang
%T Analysis of Deformation Mechanism and Risk Assessment of Tunnel in Operation
%D 2019
%R 10.11988/ckyyb.20180398
%J Journal of Yangtze River Scientific Research Institute
%P 36-42
%V 36
%N 12
%X Risk prediction models based on BP neural network and V/S analysis are proposed in this paper to evaluate the safety status and risk trend of tunnels under operation. First of all, the deformation mechanism is analyzed in line with the operating environment of the tunnel; secondly, the safety status of tunnel is assessed according to relevant safety classification standard; finally, the deformation prediction model of the tunnel is established using optimized BP neural network, and the risk development trend of tunnel is then examined based on V/S risk analysis. Case study shows that the deformation of tunnel is mainly affected by seepage, cavities, lining deterioration, and long-term stress. The safety status of the tunnel is at level V, high risk, and the risk level acquired based on settlement is higher than that of horizontal convergence. The deformation prediction result is well consistent with trend analysis result which indicates that the risk of the tunnel will further exacerbate. Both the deformation prediction model and the risk trend analysis model are verified applicable and reliable in predicting the risks of tunnel in operation.
%U http://ckyyb.crsri.cn/EN/10.11988/ckyyb.20180398