Hu Baolin, Wang Changhong
Department of Civil Engineering, Shanghai University, 333 Nanchen Road, Shanghai, 200444, China.
Heliyon. 2019 Sep 21;5(9):e02495. doi: 10.1016/j.heliyon.2019.e02495. eCollection 2019 Sep.
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 5 and 6 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.
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。我们将两种随机方法引入数值模拟。第一种方法使用经典统计计算最大地表沉降，其中利用响应面法通过一阶二次矩计算失效概率。将黏聚力、内摩擦角、杨氏模量和力学模型因子视为随机变量。第二种方法是上述三个关键岩土参数的空间随机场。使用这两种方法时，首先通过局部回归将相似的多层土转换为平稳随机场，然后进行多元空间条件离散化。通过子集蒙特卡罗算法计算最大地表沉降的失效概率。该方法应用于中国天津环湖西路站5、6号线四条重叠的盾构隧道。失效分析结果表明，岩土参数的经典统计显示出比空间随机场更高的变异性，这为复杂的盾构隧道工程提供了有力支持。
