Monitoring data-driven updating post-assessment of the effectiveness of anti-slide piles for colluvial slope stabilization

IF 3.7 2区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Bulletin of Engineering Geology and the Environment Pub Date : 2025-04-29 DOI:10.1007/s10064-025-04271-6

Yibiao Liu, Bin Liu

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引用次数: 0

Abstract

A three-dimensional monitoring data-driven updating parameter back-analysis and slope stability analysis method is proposed to quantitatively and efficiently assess the effectiveness of anti-slide piles for colluvial slope stabilization. By integrating the multi-output Gradient Boosting Decision Tree (GBDT), a meta-model is constructed to characterize the relationship between geotechnical parameters and monitored displacements. This meta-model enables deterministic and probabilistic back-analyses based on multiple monitoring points. Another meta-model is developed to characterize the relationship between geotechnical parameter field distributions and the factor of safety (FOS) using a multi-input and multi-stream Convolutional Neural Network (CNN). This meta-model enables efficient reliability analyses for colluvial slopes with highly spatially varying geotechnical parameters. The effectiveness of the proposed method is demonstrated by a typical highway colluvial slope case. The case study further reveals a linear correlation between the deterministic and reliability analysis-based ratios of safety margins. This finding suggests that both deterministic and reliability analysis outcomes can provide quantitative bases for stability assessment.

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滑坡边坡抗滑桩稳定性后评价的监测数据更新

提出了一种三维监测数据驱动的更新参数反分析与边坡稳定性分析方法，以定量、高效地评价抗滑桩对滑坡边坡的稳定效果。通过整合多输出梯度提升决策树（GBDT），构建了岩土参数与监测位移之间关系的元模型。该元模型支持基于多个监测点的确定性和概率性反向分析。利用多输入多流卷积神经网络（CNN）建立了岩土参数场分布与安全系数（FOS）关系的元模型。该元模型能够对具有高度空间变化的岩土参数的滑坡边坡进行有效的可靠性分析。通过一个典型的公路崩落边坡实例验证了该方法的有效性。案例研究进一步揭示了基于确定性和可靠性分析的安全裕度比率之间的线性相关性。这一发现表明，确定性和可靠性分析结果都可以为稳定性评估提供定量依据。

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来源期刊

Bulletin of Engineering Geology and the Environment 工程技术-地球科学综合

CiteScore

7.10

自引率

11.90%

发文量

445

审稿时长

4.1 months

期刊介绍： Engineering geology is defined in the statutes of the IAEG as the science devoted to the investigation, study and solution of engineering and environmental problems which may arise as the result of the interaction between geology and the works or activities of man, as well as of the prediction of and development of measures for the prevention or remediation of geological hazards. Engineering geology embraces: • the applications/implications of the geomorphology, structural geology, and hydrogeological conditions of geological formations; • the characterisation of the mineralogical, physico-geomechanical, chemical and hydraulic properties of all earth materials involved in construction, resource recovery and environmental change; • the assessment of the mechanical and hydrological behaviour of soil and rock masses; • the prediction of changes to the above properties with time; • the determination of the parameters to be considered in the stability analysis of engineering works and earth masses.