Prediction of surface settlement caused by synchronous grouting during shield tunneling in coarse-grained soils: A combined FEM and machine learning approach

IF 8.2 1区 工程技术 Q1 ENGINEERING, CIVIL
Chao Liu , Zepan Wang , Hai Liu , Jie Cui , Xiangyun Huang , Lixing Ma , Shuang Zheng
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引用次数: 0

Abstract

This paper presents a surrogate modeling approach for predicting ground surface settlement caused by synchronous grouting during shield tunneling process. The proposed method combines finite element simulations with machine learning algorithms and introduces an intelligent optimization algorithm to invert geological parameters and synchronous grouting variables, thereby predicting ground surface settlement without conducting numerous finite element analyses. Two surrogate models based on the random forest algorithm are established. The first is a parameter inversion surrogate model that combines an artificial fish swarm algorithm with random forest, taking into account the actual number and distribution of complex soil layers. The second model predicts surface settlement during synchronous grouting by employing actual cover-diameter ratio, inverted soil parameters, and grouting variables. To avoid changes to input parameters caused by the number of overlying soil layers, the dataset of this model is generated by the finite element model of the homogeneous soil layer. The surrogate modeling approach is validated by the case history of a large-diameter shield tunnel in Beijing, providing an alternative to numerical computation that can efficiently predict surface settlement with acceptable accuracy.

预测粗粒土盾构掘进过程中同步注浆引起的地表沉降:有限元和机器学习相结合的方法
本文提出了一种代用建模方法,用于预测盾构隧道掘进过程中同步注浆引起的地表沉降。所提出的方法将有限元模拟与机器学习算法相结合,并引入智能优化算法来反演地质参数和同步注浆变量,从而在不进行大量有限元分析的情况下预测地表沉降。基于随机森林算法建立了两个代用模型。第一个是参数反演代用模型,它将人工鱼群算法与随机森林相结合,并考虑了复杂土层的实际数量和分布。第二个模型采用实际覆盖层直径比、反演土壤参数和灌浆变量来预测同步灌浆过程中的地表沉降。为避免输入参数因上覆土层数量而发生变化,该模型的数据集由均质土层的有限元模型生成。北京某大直径盾构隧道的案例验证了该代用模型方法,为数值计算提供了一种替代方法,可有效预测地表沉降,且精度可接受。
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
Underground Space
Underground Space ENGINEERING, CIVIL-
CiteScore
10.20
自引率
14.10%
发文量
71
审稿时长
63 days
期刊介绍: Underground Space is an open access international journal without article processing charges (APC) committed to serving as a scientific forum for researchers and practitioners in the field of underground engineering. The journal welcomes manuscripts that deal with original theories, methods, technologies, and important applications throughout the life-cycle of underground projects, including planning, design, operation and maintenance, disaster prevention, and demolition. The journal is particularly interested in manuscripts related to the latest development of smart underground engineering from the perspectives of resilience, resources saving, environmental friendliness, humanity, and artificial intelligence. The manuscripts are expected to have significant innovation and potential impact in the field of underground engineering, and should have clear association with or application in underground projects.
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