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利用FLAC3D软件及内嵌的FISH程序语言编制相应程序,实现每个单元弱化弹性模量的自动计算及计算模型力学参数的自动更新。根据各级开挖卸荷结束后的弹性模量计算值分析弱化弹性模量的分布规律,进而划分弱化弹性模量的等效分布区域。结合PSO改进的BP神经网络算法进行反分析计算,建立各区域等效弹性模量与监测点水平位移关系的网络模型,输入此级边坡开挖卸荷监测点水平位移值到训练好的网络中反演得到区域等效弹性模量。实例应用结果表明,本文方法的计算结果合理,且具有较高的精度,适用于卸荷岩体弹性模量的弱化研究。
Using FLAC3D software and embedded FISH programming language to compile the corresponding program to realize the automatic calculation of the weakening elastic modulus and the automatic update of the mechanical parameters of the model. Based on the calculated elastic modulus after excavation unloading at all levels, the distribution of weakened elastic modulus was analyzed, and then the equivalent distribution of weakened elastic modulus was divided. Combined with PSO improved BP neural network algorithm for back analysis and calculation, establish the network model of the relationship between the equivalent elastic modulus and the horizontal displacement of the monitoring points, input the horizontal displacement value of the unloading monitoring point of the slope excavation to the trained network In the inversion, the equivalent elastic modulus is obtained. The results of practical application show that the method proposed in this paper is reasonable and has high precision and is suitable for the study of the weakening of the elastic modulus of unloading rock masses.