Improvement of Laboratory Protocols for Discontinuity Geomechanical Characterization and Investigation of the Effect of Saturation on Granite Strength
Bibliographic record
Abstract
The Nuclear Waste Management Organization of Canada (NWMO) is currently in the process of site selection for the future development of a high-level nuclear waste Deep Geological Repository (DGR), and locations with crystalline bedrock are the top candidates (Hirschorn et al. 2017). In support of this process, a study on the effects of water-saturation on the geomechanical response of granitic rock is conducted. Rock-water interactions are investigated in both intact rock and discontinuities. This topic was investigated on two different granites: Lac du Bonnet and Pointe du Bois pink granites. The results of this study show no significant correlations between strength reduction and water content in granite in compression, tension, and confined shear. In addition to the investigation of rock-water interactions, this work also presents the development of a new direct shear sample preparation procedure as well as a technique for normal loading and direct shear test data processing and interpretation: joint deformation correction and analytical representation of joint pre-yield deformation. An exponential function is suggested to determine the instantaneous normal and shear stiffness values.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".