Using true-triaxial stress path to simulate excavation-induced rock damage: a case study
Bibliographic record
Abstract
Abstract This study presents an example illustrating the role of in situ 3D stress path method in simulating the roof damage development observed in the Mine-by tunnel at Underground Research Laboratory (URL) located in Manitoba, Canada. The 3D stress path, at the point 1 cm in the crown of the Mine-by tunnel, was applied to a cubic Lac du Bonnet (LdB) granite sample to further understand the roof damage process and the associated seismicity. After careful calibrations, a numerical model was used to reproduce the experiment, which produced similar seismicity processes and source mechanisms. Acoustic emission (AE) events obtained from laboratory and numerical modeling were converted to locations in relation to the tunnel face and were compared to the field microseismicity (MS) occurring in the upper notch region of the Mine-by tunnel. The crack development and damage mechanism are carefully illustrated. The difference between tests and field monitoring was discussed. The intermediate principal stress ( σ 2 ) unloading process was carried out in numerical simulation to investigate its role in rock damage development. The results clearly showed σ 2 could play a significant role both in damage development and failure mode. It should be considered when predicting the damage region in underground excavations. This study highlights the potential role of laboratory and numerical stress path tests to investigate fracture processes and mechanisms occurring during engineering activities such as tunnel excavation.
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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 | 0.001 | 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".