Surface settlement prediction and application of short-distance twin-bore tunnels
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摘要: 预测近距离双孔地铁隧道施工时地表沉降位移及变形，对于预防施工过程中地表沉降所引发的动态灾害具有重要意义。对随机介质理论进行研究，综合考虑隧道断面收敛模式、隧道空间位置和隧道不同断面类型的情况，提出了随机介质理论优化算法。结合三个工程案例对比分析隧道施工中沉降监测数据与理论预测值的准确性。研究表明：随机介质理论优化算法适用条件为间跨比（L/B）小于7；优化算法预测曲线与沉降监测曲线变化趋势及最大沉降位置基本一致，理论预测曲线沉降槽宽度与沉降监测曲线沉降槽宽度基本吻合，具有良好的一致性，可以为工程提供一定参考。Abstract: Accurate prediction of ground surface settlement and displacement during the construction of closely spaced twin-bore metro tunnels is critical for mitigating dynamic hazards induced by subsurface excavation. This study refines the stochastic medium theory by developing an optimized algorithm that integrates three key factors: tunnel cross-section convergence modes, spatial positioning of twin-bore tunnels, and variations in tunnel cross-sectional geometries. Validation was conducted through comparative analysis of settlement monitoring data and theoretical predictions across three engineering case studies. The findings demonstrate that the optimized algorithm applies to scenarios where the span-to-breadth ratio (L/B) is below 7. The stochastic medium simplified theoretical prediction curve and the settlement monitoring curve are better fitted, the maximum settlement position and the trend is consistent with the settlement monitoring curve. The theoretical prediction curve settlement groove width is consistent with the settlement monitoring curve settlement groove width. The optimal algorithm and the settlement monitoring data have good consistency, which can provide reference for the project.
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