Laboratory Strength Testing of Argillaceous Limestone Under Varying Saturation, Scale, Loading Rate, and Confinement Conditions
Bibliographic record
Abstract
The Deep Geological Repository (DGR) concept is the proposed solution for the long-term storage of nuclear waste in Canada. While site selection processes are currently underway for high-level waste storage, a low and intermediate waste storage DGR is planned for development at depth in Kincardine, Ontario. The DGR site is to be hosted in the Cobourg limestone, a rock formation which presents varying heterogeneity at different scales. The successful design of long-term nuclear waste storage requires engineered barriers and geology designed to safely and securely contain contaminants. The excavation of hard rocks at depth can induce damage to the surrounding rock mass. This damage corresponds to the initiation and propagation of fractures and is related to in situ stress conditions and excavation processes. Heterogeneous rock masses can further complicate the initiation and propagation of fractures, causing inconsistent behaviour related to the variability of the rock. The changing in situ conditions of DGR host rocks can also influence fracture behaviour, highlighting the need for a better understanding of the effect of rock conditions on the damage behaviour of brittle rocks. This research examines the influences of various testing conditions on the geomechanical properties of Cobourg limestone, to address the changing in situ conditions that may be present during long-term storage of nuclear waste. The effects of specimen saturation, scale, loading rate, and confinement have been investigated through the laboratory strength testing of specimens representative of Cobourg limestone found at depth for the proposed low and intermediate level DGR site. Using standardized laboratory testing practices and newly developed experimental methodologies, this thesis describes the influences of testing condition on the elastic and strength properties of the rock. The testing methodology is presented and examined to evaluate the effectiveness of the different testing conditions in properly characterizing the Cobourg limestone. The observations and results from this work provide details regarding the physical properties and failure behaviour of the rock, as well as non-standard testing techniques for investigating heterogeneous rock masses. This research provides insight into the characterization of brittle rock failure under different testing conditions, which is important for future DGR site selection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".