Back Analysis of Mechanical Parameters of Surrounding Rock in Deep Roadway Based on BP Neural Network
Based on the principle of BP neural network algorithm,the back analysis model of mechanical parameter displacement of surrounding rock of deep roadway is established with the help of MATLAB r2021b neural network toolbox.The learning samples of neural network are established by using orthogo-nal test and FLAC3D numerical simulation software.The cohesion,internal friction angle,Poisson's ratio and elastic modulus of four mechanical parameters of deep tunnel surrounding rock are calculated in reverse direction.The results show that by substituting the parameter inversion results into the FLAC3D finite el-ement numerical simulation software,the calculated roadway vault settlement and two side convergence values are very close to the actual monitoring values,with small relative error and high precision.The me-chanical parameters of sedimentary rocks obtained by this method are useful.More precise rock mechanical parameters of the deep roadway can be obtained,so as to provide a scientific basis for the overall layout of deep roadway and roadway design support.
BP neural networknumerical simulationdisplacement back analysisroadway construction
万方数据
维普
