Effect of seepage forces on tunnel face stability
Bibliographic record
Abstract
In this study, two factors are simultaneously considered for assessing tunnel face stability. The first is the effective stress acting on the tunnel face calculated by upper bound solution, and the other is the seepage force calculated by numerical analysis under the condition of steady-state groundwater flow. The seepage forces calculated by numerical analysis are compared with the results of a model test. The upper bound solution taking into consideration the seepage force acting on the tunnel face, shows that the minimum support pressure for the face stability is equal to the sum of the effective support pressure that is obtained from the upper bound solution based on effective stress and the seepage pressure acting on the tunnel face. It was found that the average seepage pressure acting on the tunnel face is proportional to the hydrostatic pressure at the same elevation, and the magnitude is about 22% of the hydrostatic pressure for the drainage type tunnel and about 28% for the waterproof type tunnel. The seepage forces obtained from the results of a model test showed similar trends as those calculated by numerical analysis.Key words: face stability, upper bound solution, seepage force, model test.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".