摘要
Abstract
Based on the project of East Taiping Mountain Tunnel in Zhangjiakou City,a finite element model with MIDAS software was established.GA-BP neural network by use of annealing algorithm was optimized,and then orthogonal test and construct GASA-BP neural network to was designed.According to the values of simulations of tunnel arch roof settlement,horizontal convergence and invert arch uplift,the inversion analysis on elastic modulus,cohesive strength and internal friction angle of the surrounding rock were carried out.The results show that,for the value of simulation of tunnel arch roof settlement,horizontal convergence and invert uplift,which is obtained from the inversion by use of GASA-BP neural network,and the value of the actual monitoring,the maximum difference between them are 6.60％,19.80％and 2.16％,respectively.Compared with BP neural network,GASA-BP neural network can provide higher accuracy of inversion,and the precision of surrounding rock parameters obtained by the inversion is within a reasonable range.The finite element model established under these parameters can contribute to good simulation of engineering practice.关键词
隧道工程/破碎围岩/神经网络/退火算法/反演分析/正交试验/沉降监测/围岩参数Key words
tunnelling/broken rock/neural network/annealing algorithm/inversion analysis/orthogonal test/settlement monitoring/parameter of surrounding rock分类
交通工程
