An Improved Time-Dependent Convergence Confinement Method for Estimation of Tunnel Support Loads in Squeezing Ground Conditions
Bibliographic record
Abstract
ABSTRACT: In tunnel construction, the total tunnel wall displacement increases due to face advancement and the time-dependent behavior of the surrounding rock mass. The convergence confinement method (CCM) is one of the approaches used to analyze the interactions between tunnel wall displacement and support load. CCM utilizes either analytical closed-form solutions or empirical Longitudinal Displacement Profiles (LDP); however, it usually neglects the influence of time-dependency of ground response and associated gradually increasing deformations even after the excavation stage. Designing the tunnel support system without consideration of the time-dependent deformation may result in a false selection of the installation time and the support system type, causing safety issues, cost overruns, and project delays. This paper focuses on discussing a revised CCM to estimate the tunnel's support system loads in a geomaterial with squeezing characteristics and tunnel wall converges significantly with time. The proposed methodology is based on the outcomes of the physical model test results and observations from the tunnels that have experienced squeezing in different parts of the world. The initial section of this paper elucidates the Convergence Confinement Method (CCM) and outlines enhancements aimed at broadening its applicability to squeezing tunnels. The subsequent portion of the paper details the validation process of proposed method, followed by a systematic approach to designing tunnel support systems in squeezing ground. 1. INTRODUCTION Tunnels in squeezing ground experience significant deformations even after the excavation (Barla, 1995). The load the converging rock mass/soil imposes on the tunnel support system also increases gradually. The support required to stabilize the tunnel boundary in squeezing ground can be two to three times the thickness/stiffness of the support for the same tunnel in non-squeezing conditions (Jethwa et al., 1984). Estimating the deformations due to squeezing beforehand is vital to ensure safe, efficient, and economical tunnel construction (Barla, 2001). The primary reason for the squeezing ground conditions is the presence of clay minerals in a geological unit with a low strength ratio to the in-situ stress at the tunnel location (Terzaghi, 1946; Wood, 1972). Some of the notable examples of such tunnels include the John Street Pumping Station Tunnel in Canada (Lo et al., 1987), the Still Water Tunnel in the United States (Phien-wej & Cording, 1991), the Uluabat Project Tunnel in Turkey (Bilgin & Algan, 2012), and the Laodongshan Tunnel in China (Cao et al., 2018).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".