Effects of the skew angle of new tunneling on an existing tunnel: three-dimensional centrifuge and numerical modeling
Bibliographic record
Abstract
Tunneling results in stress relief and arching in the ground. New tunnel excavation beneath an existing tunnel but at different angles can lead to different patterns of stress redistribution. Studies on multitunnel interaction have mainly focused on perpendicular tunnels, and the effects of tunneling skew angle remain poorly understood. Three-dimensional centrifuge modeling and numerical back-analyses were conducted to investigate the effects of twin-tunnel interaction at three skew angles (30°, 60°, and 90°). The effects of new tunnel excavation on an existing tunnel were simulated by controlling tunnel volume and weight losses in-flight. A hypoplastic soil model capable of simulating path-dependent and strain-dependent soil stiffness was adopted for the numerical back-analyses. Distinct load redistribution patterns were identified to explain deformations of the existing tunnel at different skew angles due to the advancement of the new tunnel. For 90° tunneling, hoop force increased at the crown and decreased at the left springline of the existing tunnel. The opposite responses were identified at 30° tunneling. A critical skew angle of 30° tunneling led to the maximum invert settlement and tunnel deformation of the existing tunnel. At 30° tunneling, the induced strain in the tunnel lining was 2.3 times larger than that of tunneling at 90°, exceeding the cracking limit suggested by the American Concrete Institute.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".