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

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.

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Publication Details

Journal
Underground Space
Published
2025-08-11
DOI
https://doi.org/10.1016/j.undsp.2025.04.009
Citations
1
Primary Topic
Geotechnical Engineering and Analysis
Type
article
Field-Weighted Citation Impact
1.30

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article

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

Zipeng Ma, Haibin Wei, Fuyu Wang, Boyu Jiang et al.
1 citations
Underground Space
Geotechnical Engineering and Analysis
1.30
article

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

Zipeng Ma, Haibin Wei, Fuyu Wang, Boyu Jiang, Dongsheng Wei
article en
1 citations

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.

Underground SpaceVol. 24
Jilin University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 18%
Geotechnical Engineering and Analysis
1.30
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