The effect of pore-water pressure on NATM tunnel linings in decomposed granite soil
Bibliographic record
Abstract
Tunnelling in a water bearing soil often produces a long-term interaction between the tunnel lining and the surrounding soil. With respect to lining design, infiltration and external pore-water pressures are often one of the most important factors to be considered. Development of pore-water pressure may accelerate leakage and cause deterioration of the lining. This can be particularly troublesome to structural and functional components of the tunnel and can often lead to structural failure. However, as a result of the complicated hydraulic boundary conditions and the long times often required for pore pressure equilibration, research on this subject is scarce. Consequently, most design approaches deal with the effects of pore-water pressure on the tunnel lining in a qualitative manner. In this paper, the development of pore-water pressure and its potential effects on the tunnel lining are investigated using the finite element method. In particular, the deterioration of a drainage system caused by clogging is considered. It is shown that the development of pore-water pressure on the lining is dependent on the lining permeability and the deterioration of the drainage system, particularly for a tunnel with both a primary and a secondary lining. The magnitude of pore-water pressure on a new Austrian tunnelling method (NATM) tunnel constructed in decomposed granite soil and the effect of tunnel shape are investigated. Design curves for estimating pore-water pressure loads on a secondary lining are proposed.Key words: numerical analysis, tunnel lining, decomposed granite.
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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 | 0.001 |
| 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 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".