The role of rock engineering in developing a deep geological repository in sedimentary rocks
Bibliographic record
Abstract
The Government of Canada is now considering the use of deep geologic repositories (DGRs) for the storage of spent nuclear fuel. The DGR will be comprised of a series of underground openings, access tunnels, placement rooms, and other excavation area. Several conceptual designs for the DGRs are being considered. This study provided an overview of the role of rock engineering in the siting, design and construction of DGRs in sedimentary rocks. Rock engineering uses rock mechanics and engineering geology principles to resolve problems related to structures constructed in or composed of rock and other geomaterials. Data, tools and techniques required to optimize DGR development were also reviewed, and information on rock mechanical properties and in situ stress measurements for the Michigan Basin were provided. Results of the study demonstrated that rock engineering will play an important role in the various stages of DGR development as well as during post-construction monitoring activities. It was concluded that the review will provide the basis for further research on DGR siting, design and construction in Canada. 26 refs., 5 figs.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".