Estimating settlements due to TBM tunnelling

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Victor Hugo Franco Rattia, S. Divall, G. Gitirana, A. Assis
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引用次数: 0

Abstract

Soft-ground Tunnel Boring Machines (TBM) are the preferred solution for construction of long tunnels and linear infrastructure assets, especially in urban areas. TBMs allow the control of tunnel face stability, minimizing effects on the surrounding ground. Unfortunately, the existing methods for the assessment of ground surface movements due to TBM tunnelling either utilise complex and computationally expensive numerical analyses or rely on simplistic volume loss theories, which do not consider characteristics of the ground and TBM operation. This paper presents a simple formulation to estimate the immediate surface settlement due to the applied TBM support pressure, based on an analogy with the hyperbolic behaviour of stress-strain curves of soils. The maximum surface settlement and volume loss were the variables chosen to describe the ground movement while the TBM face support pressure describes the tunnel internal support pressure. Uncertainties due to the inherent variability of geotechnical parameters were also considered, resulting in definition of lower and upper boundaries. Data from a series of centrifuge test results, with and without tunnel face reinforcement by forepoles and a real scale TBM case study were used to validate the proposed model. The analyses show that the proposed model adequately represented the observed settlement data.
估计隧道掘进机开挖引起的沉降
软土地基隧道掘进机(TBM)是建设长隧道和线性基础设施资产的首选解决方案,特别是在城市地区。隧道掘进机可以控制隧道工作面稳定性,最大限度地减少对周围地面的影响。不幸的是,现有的评估隧道掘进机开挖引起的地表移动的方法要么使用复杂且计算成本高昂的数值分析,要么依赖简单的体积损失理论,而这些理论没有考虑到地面和隧道掘进机运行的特征。本文根据土的应力-应变曲线的双曲特性,提出了一个简单的公式来估计由于施加TBM支护压力而引起的地表立即沉降。地表最大沉降量和体积损失是描述地表移动的变量,掘进机工作面支护压力是描述巷道内部支护压力的变量。还考虑了岩土参数固有变异性带来的不确定性,从而确定了下边界和上边界。利用一系列离心机试验结果的数据,包括前杆加固和不加固隧道工作面,以及一个实际规模的TBM案例研究,来验证所提出的模型。分析表明,该模型能较好地反映实测沉降数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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