Investigation into the influence of excavation of twin-bored tunnels within weak rock masses adjacent to slopes
Bibliographic record
Abstract
The focus of this investigation is twin tunnelling projects designed and constructed adjacent to slopes. To this end, several state-of-the-art two-dimensional (2-D) and three-dimensional (3-D) numerical models for multiple scenarios were utilized. The novelty of this research (further highlighted by two case studies) explicitly demonstrates that for 2-D and 3-D elastic and plastic analyses for weak rock masses, the interaction between the two tunnel branches for various conditions show how the pillar width minimally influences such interaction past two diameter widths of separation. As well, the 3-D sequential longitudinal tunnel excavation of the twin tunnel does not significantly influence the crown displacements of the two tunnels prior to construction of the mid-span of the twin tunnel. Slope stability analysis was conducted by employing the novel shear strength reduction (SSR) method. These findings confirm that changes in the location of the twin tunnels with respect to the slope and one another in combination with the natural angle of the slope can improve the overall stability without any other special measures taken. As well, by having the twin tunnel pillar width constant, the vertical translation of the tunnels (i.e., increase in the overburden) is more beneficial than that of a horizontal translation, resulting in a higher factor of safety.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".