Enhancing understanding of 3D rectangular tunnel heading stability in c-φ soils with surcharge loading: A comprehensive FELA analysis using three stability factors and machine learning

Artificial Intelligence in Geosciences Pub Date : 2025-03-14 DOI:10.1016/j.aiig.2025.100111

Suraparb Keawsawasvong , Jim Shiau , Nhat Tan Duong , Thanachon Promwichai , Rungkhun Banyong , Van Qui Lai

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Abstract

This study examines the stability of three-dimensional rectangular tunnel headings in drained c-ϕ soils, incorporating surcharge effects using 3D Finite Element Limit Analysis (FELA). It focuses on the upper and lower bound solutions for three stability factors: cohesion, surcharge, and soil unit weight (Nc, Ns, and Nγ). Based on Terzaghi's principle of superposition, the analysis evaluates tunnel stability under varying parameters, such as cover-depth ratio (H/D), width-depth ratio (B/D), and friction angle (ϕ). The results align closely with previous studies, and practical design charts are provided for calculating minimum support pressures. Additionally, machine learning models (ANN and XGBoost) are used to develop accurate correlations between input parameters and stability results. A relative importance index analysis is conducted to assess the impact of these parameters. This research enhances understanding of tunnel stability and offers practical insights for tunnel design.

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加强对具有附加荷载的 c-φ 土层中三维矩形隧道顶稳定性的理解：利用三个稳定因子和机器学习进行综合 FELA 分析

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