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周鹏远, 宋战平, 王军保, 张玉伟, 田小旭. 基于随机介质理论的偏压隧道地表沉降预测方法[J]. 岩土工程学报, 2025, 47(3): 589-598. DOI: 10.11779/CJGE20231121
引用本文: 周鹏远, 宋战平, 王军保, 张玉伟, 田小旭. 基于随机介质理论的偏压隧道地表沉降预测方法[J]. 岩土工程学报, 2025, 47(3): 589-598. DOI: 10.11779/CJGE20231121
ZHOU Pengyuan, SONG Zhanping, WANG Junbao, ZHANG Yuwei, TIAN Xiaoxu. Prediction method for ground surface settlement induced by bias tunnel based on stochastic medium theory[J]. Chinese Journal of Geotechnical Engineering, 2025, 47(3): 589-598. DOI: 10.11779/CJGE20231121
Citation: ZHOU Pengyuan, SONG Zhanping, WANG Junbao, ZHANG Yuwei, TIAN Xiaoxu. Prediction method for ground surface settlement induced by bias tunnel based on stochastic medium theory[J]. Chinese Journal of Geotechnical Engineering, 2025, 47(3): 589-598. DOI: 10.11779/CJGE20231121

基于随机介质理论的偏压隧道地表沉降预测方法

Prediction method for ground surface settlement induced by bias tunnel based on stochastic medium theory

  • 摘要: 隧道开挖引起地表沉降的各种预测方法均假定隧道收敛模式为对称形式,忽略了隧道非对称收敛的影响。为对偏压隧道引起地表沉降进行预测,提出了一种新的隧道偏压收敛模式,定义了相应的偏压参数 \theta , \gamma _1 , \gamma _3 ,基于随机介质理论,利用坐标变换和二重积分的数值化处理,得到了偏压隧道引起地表沉降的预测模型;通过实际工程案例,验证了该方法的适用性,并分析了相关参数对地表沉降的影响规律。提出的预测模型将传统对称收敛模式拓展至非对称情况,能很好预测地表沉降的非对称趋势,且更接近实际案例的监测数值。

     

    Abstract: The disturbance of the surrounding soil by tunnel excavation will inevitably lead to surface settlement. When calculating the surface settlement caused by tunnel excavation, various prediction methods have assumed that the tunnel convergence mode is bilaterally symmetrical. This assumption ignores the influences of asymmetric convergence of the tunnel, and the resulting surface settlement is also symmetrically distributed. In order to predict the surface settlement caused by a bias tunnel, a new tunnel bias convergence mode is proposed, and the corresponding bias parameters \theta , \gamma _1 and \gamma _3 are defined. Based on the stochastic medium theory, a prediction model for the surface settlement caused by the bias tunnel is obtained using the coordinate transformation and double-integral numerical processing. Through actual engineering cases, the applicability of this method is verified, and the influences of the relevant parameters on the surface settlement are analyzed. The proposed model extends the traditional symmetric convergence mode to asymmetric situations, can well predict the asymmetric trend of surface settlement, and it is closer to the monitoring values of actual cases.

     

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