Numerical Simulation Analysis of Highway Tunnel Excavation Based on Artificial Intelligence Algorithm

Dong-xia Liu
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Abstract

In the numerical simulation of highway tunnel excavation, it is difficult to calculate the yield criterion of rock and soil in traditional calculation, which leads to the lack of individual parameters in the final numerical simulation results, resulting in the low overall stability of tunnel deep foundation section, rebound rate of deep foundation pit bottom and limit equilibrium rate of supporting pile. Therefore, a numerical simulation analysis method of highway tunnel excavation based on artificial intelligence algorithm is proposed. Firstly, the damage stage method is used to confirm the surrounding rock pressure parameters. After confirming the stability of the surrounding rock, the seismic factors of the highway tunnel are considered to determine the buried depth of the tunnel. The yield function is used to calculate the yield criterion of geotechnical materials. Finally, the artificial intelligence algorithm is used for numerical simulation. The simulation results show that the overall stability of the tunnel deep foundation section, the rebound rate of the deep foundation pit bottom and the limit equilibrium rate of the supporting pile are high.
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基于人工智能算法的公路隧道开挖数值模拟分析
在公路隧道开挖数值模拟中,传统计算中难以计算岩土屈服准则,导致最终数值模拟结果缺乏个别参数,导致隧道深基坑断面整体稳定性、深基坑底部回弹率和支护桩极限平衡率较低。为此,提出了一种基于人工智能算法的公路隧道开挖数值模拟分析方法。首先,采用损伤阶段法确定围岩压力参数;在确定围岩稳定性后,考虑公路隧道的地震因素,确定隧道埋深。利用屈服函数计算岩土材料的屈服准则。最后,利用人工智能算法进行了数值模拟。模拟结果表明,隧道深基坑段整体稳定性、深基坑底部回弹率和支护桩极限平衡率较高。
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