Parametric Study and Optimization of Longitudinal Bolting in Tunnel Face Reinforcement
Bibliographic record
Abstract
Longitudinal bolting has emerged as an effective pre-confinement technique to reinforce tunnel faces, offering advantages over alternative methods by directly enhancing stability in the excavation direction and improving load transfer to the surrounding ground.Despite its practical use, the influence of key design parameters remains insufficiently quantified for optimization.This study addresses this gap through a three-dimensional numerical model that incorporates soil-bolt interaction, with the soil represented by the Mohr-Coulomb failure criterion and the bolts modeled as linear elastic elements.A systematic parametric study was performed to evaluate the effects of bolt density, embedded length, axial stiffness, and soil strength on tunnel face stability.The results demonstrate that increasing bolt density significantly reduces face extrusion and axial displacement, although the rate of improvement diminishes beyond 0.25 bolts/m .Force distribution analysis revealed three distinct zones: confinement (0-0.5R),anchorage (0.5R-2.5R), and inert (>2.5R).The factor of safety was shown to reach its optimum at a bolting density of 0.25 bolts/m , providing a balance between reinforcement efficiency and material economy.These findings not only clarify the mechanisms governing longitudinal bolting efficiency but also deliver practical guidelines for the design and optimization of tunnel face reinforcement systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".