Constitutive model development and field simulation of excavation damage in bedded argillaceous rock
Bibliographic record
Abstract
Argillaceous rocks are candidate host and/or cap formations for the geological disposal of nuclear wastes in many countries, including Canada, France and Switzerland. The understanding of the long term mechanical behaviour of such rocks is an essential requirement for the assessment of their performance as a barrier against radionuclide migration. Due to the existence of bedding, argillaceous rocks are inherently anisotropic and the development of stress-strain models for their mechanical behaviour needs to take this anisotropy into account. This paper presents two examples of the practical implementation of stress-strain relationships in finite element models to simulate the excavation damage zones (EDZ) in bedded argillaceous rocks. The first example concerns the EDZ around a micro-tunnel in Opalinus Clay, in Switzerland. The second example relates to the EDZ around the century-old tunnel in Tournemire shale, in France. Both examples show the importance of developing robust stress-strain models that can replicate inherent anisotropy of the rock, and of calibrating and validating the models with a comprehensive set of laboratory experiments. The second example shows the additional influence of dessication and fault zone on the extent and shape of the EDZ.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".