Experimental and Numerical Investigation of the Effect of Rock Mass Behavior and Stratum Orientations on Horseshoe‐Shaped Tunnel Stability
Bibliographic record
Abstract
ABSTRACT This study investigates tunnel stability within sedimentary rock masses characterized by multiple joint sets and challenging geological conditions. The behavior of stratified rock masses around an excavation depends on both the intact rock and the combination of dominant and bedding joints. The main objective of this study is to highlight the convergence and deformation in rock masses around horseshoe‐shaped tunnels using an integrated methodology that combines field investigations, finite element modeling, and pull‐out test results. Statistical analysis confirmed the robustness of the 3D modeling approach for reproducing in situ behavior and creating realistic models of heterogeneous, anisotropic rock masses. The numerical results indicate that the highest displacement ratio is concentrated at the intersection of the bedding and dominant joints with dip angles ranging from 0° to 45°, which should be considered as critical dip angles for mining progress. Indeed, wedge and sliding failure zones developed on the roofs and left rib, respectively. Increasing depth reduced the influence of rock mass quality, particularly for GSI chart values ranging between 35 and 40, resulting in significant convergence around the excavation. The support system emphasizes the effectiveness of systematic bolting in competent rock masses. Moreover, the pull‐out tests revealed that the load‐bearing capacity of the split‐set bolts increased substantially when the bedding approached vertical orientations θ = 90°, and the compressive strength exceeded 39.6 MPa, conditions that promote safer tunneling through vertical stratum orientations. These findings enhance the understanding of tunneling stability mechanisms in stratified rock masses with multiple joint sets under various geological conditions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".