双连拱隧道围岩变形有限元与BP神经网络耦合分析

Coupling analysis of surrounding rocks in double-arch tunnel by FE and BP neural networks

以浙江金(华)—丽(水)—温(州)高速公路永嘉鹿城段的红枫双连拱隧道为工程背景,建立了基于神经网络的连拱隧道围岩变形预测模型。利用施工过程中左洞量测的围岩变形进行反分析,确定出围岩的力学特性参数,再通过数值分析方法对隧道右洞围岩变形和稳定性做出合理的评价和符合实际的预测,从而更有效地对支护参数和施工方法进行反馈设计。通过预测值与实际监测值的比较可以看出,其预测精度满足岩土工程的要求,具有一定的工程意义。

A deformation prediction model of surrounding rocks in double-arch tunnel based on BP neural network was established with a practical project. Mechanical parameters of surrounding rocks were obtained by back analysis method based on measured data in left tunnel. Deformation prediction and stability analysis of surrounding rocks in right tunnel were carried out by f＇mite dement analysis. The proposed prediction model made feedback design on supporting parameters and construction method more effective. By Comparison, it is shown that the results of prediction are in good agreement with those measured in situ. It can meet the requirement of geotechnical engineering.