偏压双连拱公路隧道围岩稳定性动态预测分析

由于高速公路偏压双连拱隧道的复杂地质条件,会给隧道安全施工带来严重威胁,提出在加强隧道开挖现场监控量测的基础上,以位移量测结果作为学习样本,应用BP神经网络预测隧道围岩位移的大小,分析围岩的稳定性.由于BP神经网络能综合考虑隧道围岩节理、裂隙等对围岩位移的影响,所以与有限元反分析法计算隧道围岩位移结果比较,显示BP神经网络预测结果的误差较小,预测值与实际测量值趋于一致,因此应用BP网络预测偏压双连拱隧道围岩位移,超前分析其稳定性是安全可靠的,该预测方法的预测结果可以指导现场的施工.

Dynamic Prediction Analysis of Surrounding Rocks Stability for Non-symmetric Double-Arch Highway Tunnel

During the construction of non-symmetric double-arch rock highway tunnel, the complicated geological condition may affect the safety of the constructor and the engineering quality. In this paper, two treatment methods are put forward. At first, the site monitoring of surrounding rock displacement must be carried out, then, BP neural network is applied in predicting the displacement of surrounding rock based on the learning sample of measured value, so the stability of surrounding rocks may be analyzed and forecasted. During the analysis of BP neural network, the effects of joint and fracture of surrounding rock on displacement can be comprehensively considered, comparing the predicted values of displacement with those by FEM. The results show that not only the predicted error of BP neural network is relative small, but the predicted values of surrounding rock displacement are close to measured ones. So, the predicted values of BP neural network are reliable and may guide the engineering construction in site.