Interlayer soil settlement prediction in the construction of under-crossing existing structures based on multi-parameter time series model

IF 8.3 1区 工程技术 Q1 ENGINEERING, CIVIL
Boyu Jiang, Haibin Wei, Dongsheng Wei, Zipeng Ma, Fuyu Wang
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引用次数: 0

Abstract

Predicting surface settlement can identify potential risks associated in shield construction. However, in the construction of under-crossing existing structures, the surface settlement is minimal due to the high stiffness of the existing structure, making it unsuitable as a basis for risk assessment. Therefore, interlayer soil settlement was used as an evaluation index in this paper, which was predicted by the developed multi-parameter time series (MPTS) model. This model establishes new dataset, including time, effective stress ratio (ESR), mechanical fluctuation coefficient (MFC), and interlayer soil settlement, where ESR and MFC take into account the changing geological conditions. This study proposes a novel MPTS model, integrating grid search (GS), nonlinear particle swarm optimization (NPSO), and support vector regression (SVR) algorithms to predict interlayer soil settlement during under-crossing construction. It utilizes GS and NPSO to obtain the optimal hyperparameters for SVR. Sensitivity analysis based on MPTS model was used to identify important parameters and propose specific improvement measures. A real under-crossing tunnel project was adopted to verify the effectiveness of the MPTS. The results show that the new input parameters proposed in this paper reduce mean absolute error (MAE) by 20.3% and mean square error (MSE) by 46.7% of prediction results. Compared with the other three algorithms, GS-NPSO-SVR has better prediction performance. Through Sobol sensitivity analysis, previous settlement, ESR and MFC in fully weathered mudstone and moderately weathered mudstone are identified as the primary parameters affecting the interlayer soil settlement. The improvement measures based on analysis results reduce the accumulated settlement by 79.97%. The developed MPTS model can accurately predict the interlayer soil settlement and provide guidance for water stopping or reinforcement construction.
基于多参数时间序列模型的下穿既有结构施工层间土体沉降预测
预测地表沉降可以识别盾构施工中的潜在风险。然而,在下穿既有结构施工中,由于既有结构的高刚度,地表沉降最小,不适合作为风险评估的依据。因此,本文以层间土体沉降为评价指标,采用建立的多参数时间序列(MPTS)模型对层间土体沉降进行预测。该模型建立了新的数据集,包括时间、有效应力比(ESR)、机械波动系数(MFC)和层间土体沉降,其中ESR和MFC考虑了地质条件的变化。本文提出了一种新的MPTS模型,结合网格搜索(GS)、非线性粒子群优化(NPSO)和支持向量回归(SVR)算法来预测下交叉施工过程中的层间土壤沉降。利用GS和NPSO来获得SVR的最优超参数。采用基于MPTS模型的敏感性分析,识别重要参数,提出具体改进措施。通过一个实际的下穿隧道工程来验证MPTS的有效性。结果表明,本文提出的新输入参数使预测结果的平均绝对误差(MAE)降低了20.3%,均方误差(MSE)降低了46.7%。与其他三种算法相比,GS-NPSO-SVR具有更好的预测性能。通过Sobol敏感性分析,确定了完全风化泥岩和中度风化泥岩的前期沉降、ESR和MFC是影响层间土体沉降的主要参数。根据分析结果采取的改进措施使累积沉降减少79.97%。所建立的MPTS模型能够准确预测层间土体沉降,为止水或加固施工提供指导。
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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