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Ground surface settlement analysis of shield tunneling under spatial variability of multiple geotechnical parameters

机译:多种岩土参数空间变异性下盾构隧道地表沉降分析

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摘要

This paper presents an efficient method of shield tunneling reliability analysis using spatial random fields. We introduced two stochastic methods into numerical simulation. The first one computes the maximal ground surface settlement using classical statistics, in which the response surface method is utilized to calculate the failure probability by first-order second moment. Cohesion, internal friction angle, Young's modulus and mechanical model factor are considered as random variables. The second method is the spatial random fields of aforementioned three key geotechnical parameters. Using these two methods, similar multiple soil layers are converted into a stationary random field by local regression as the first step, and then the process is followed by the spatially conditional discretization of multivariate. Failure probability of maximal ground surface settlement is calculated by a subset Monte-Carlo Algorithm. This approach is applied into the four-overlapping shield tunnels of the 5th and 6th metro lines intersecting at Huanhu W Rd station, Tianjin China. The failure analysis results indicated that classical statistics of geotechnical parameters showing higher variability than spatial random fields, which substantially support the complex shield tunneling project.
机译:本文提出了一种利用空间随机场进行盾构隧道可靠性分析的有效方法。我们在数值模拟中引入了两种随机方法。第一个方法是使用经典统计量来计算最大地面沉降量,其中使用响应面方法来计算一阶第二阶矩的破坏概率。内聚力,内摩擦角,杨氏模量和力学模型因子被认为是随机变量。第二种方法是上述三个关键岩土参数的空间随机场。使用这两种方法,第一步是通过局部回归将相似的多个土壤层转换为固定的随机场,然后进行此过程,然后进行多元的空间条件离散化。通过子集蒙特卡罗算法计算最大地面沉降的失败概率。该方法被应用于在中国天津环湖西路站相交的第5条和第6条地铁线的四个重叠的盾构隧道中。破坏分析结果表明,岩土工程参数的经典统计数据显示出比空间随机场更高的可变性,这在很大程度上支持了复杂的盾构隧道工程。

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