Design aspects of swelling of shales for tunnelling projects in Southern Ontario, Canada
Bibliographic record
Abstract
Swelling may result in excessive pressure and deformation of support system of tunnels if it is not properly investigated by testing and not accounted for in construction and support design. The Georgian Bay and Queenston Shales in Southern Ontario have been reported to have potential for swelling behavior. Swelling is driven by osmosis and diffusion processes that are originated from an outward salt concentration gradient from the rock pore fluid to the ambient fluid. It is known that even when the outward salinity difference exists and water is accessible, swelling does not occur unless the confining stresses applied to a volume of shale is below the suppression stress threshold. It is also known that swelling rate decreases over time, and therefore the maximum swelling is expected to occur in the early days and months after swelling initiation rather than in years, but still swelling strain can increase to several times of the 1-year swelling strain over the lifetime of tunnelling projects. Various constitutive models have been proposed and used in numerical codes to capture time- and confinement- dependency of swelling. In this paper, these models are briefly reviewed and different aspects of design of tunnelling projects in Southern Ontario shale formations are discussed with a few examples of recent and old projects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".