Stability Design Charts and Equations for Rectangular Tunnels Using Terzaghi's Modified Stability Factors and Machine Learning
Publication: International Journal of Geomechanics
Volume 24, Issue 10
Abstract
The objective of this study is to investigate the stability of plane strain rectangular tunnels under the effects of soil cohesion, surcharge loading, and soil unit weight. The novelty of the study is to extend Terzaghi's bearing capacity equation approach for determining three tunnel stability factors (Nc, Ns, and Nγ) that can be used to evaluate a tunnel's stability. These stability factors, functions of the coverdepth ratio (H/D), width-to-height ratio (B/D), and drained friction angle (ϕ), are employed in conjunction with the principle of superposition to assess the overall stability of a tunnel. To achieve this objective, the study employs finite-element limit analysis (FELA) with adaptive meshing techniques to ensure accurate calculations and address any disparities between the upper bound and lower bound solutions. The analysis elucidates the failure mechanisms of the tunnel and validates the results by comparing them with prior research. In addition, closed-form equations are developed to facilitate the calculation of these stability factors using machine learning methods, consisting of artificial neural network and support vector machine. The research is expected to provide valuable insights into the stability of rectangular tunnels, particularly in scenarios involving soil cohesion, surcharge loading, and varying soil unit weights. The combination of traditional geotechnical principles with modern FELA numerical methods and machine learning predictive models promises to offer a comprehensive and practical approach for tunnel stability analysis.
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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgment
We acknowledge Ho Chi Minh City University of Technology (HCMUT), VNU-HCM for supporting this study.
Author contributions: Nhat Tan Duong: Investigation, Software, Writing—original draft, Visualization, Validation, Writing—review and editing. Jim Shiau: Conceptualization, Methodology, Data curation, Visualization, Investigation, Software, Validation, Writing—review and editing. Thanachon Promwichai: Software, Writing—original draft, Visualization, Validation, Writing—review and editing. Rungkhun Banyong: Software, Writing—original draft, Visualization, Validation, Writing—review and editing. Suraparb Keawsawasvong: Conceptualization, Methodology, Data curation, Visualization, Investigation, Software, Validation, Writing—review and editing. Van Qui Lai: Conceptualization, Methodology, Supervision, Data curation, Visualization, Investigation, Software, Validation, Writing—original draft, Writing—review and editing.
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Information & Authors
Information
Published In
International Journal of Geomechanics
Volume 24 • Issue 10 • October 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Nov 14, 2023
Accepted: Apr 23, 2024
Published online: Jul 24, 2024
Published in print: Oct 1, 2024
Discussion open until: Dec 24, 2024
ASCE Technical Topics:
- Analysis (by type)
- Artificial intelligence and machine learning
- Cohesive soils
- Computer programming
- Computing in civil engineering
- Design (by type)
- Engineering fundamentals
- Failure analysis
- Finite element method
- Geomechanics
- Geotechnical engineering
- Load factors
- Methodology (by type)
- Numerical analysis
- Numerical methods
- Soil dynamics
- Soil mechanics
- Soil stabilization
- Soils (by type)
- Structural design
- Structural engineering
- Tunnels
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