A laboratory-based approach to assess rockbolt behaviour in shear
Bibliographic record
Abstract
Epoxy-bonded rebar is commonly used to support the roof of an underground potash mine. The rebar is often loaded in tension, but in certain circumstances, the potash can load the rebar in shear or by a combination of tension and shearing. Rebar failure due to tension has been studied previously and is well understood. A laboratory test procedure has been developed to help quantify rebar shear behaviour. The rebar is tested by bonding it in three segments of steel pipe and applying a lateral load to the centre segment. These tests isolate the rebar–epoxy interaction from the highly variable effect of the surrounding potash. The test method also allows for an easy and controlled comparison of different sizes of rebar, grades of rebar steel, and aperture between the pipe sections; all of which can significantly affect the behaviour of rebar in shear. The data gathered during each test includes the load and displacement. However, distributed optical strain sensing is also being used, which allows for strain measurements at 0.5 mm resolution along the length of the rebar. This technology allows for detailed insight into rebar behaviour. The International Minerals Innovation Institute (IMII), PotashCorp, The Mosaic Company, Agrium Inc., as well as Natural Sciences and Engineering Research Council of Canada (NSERC) are sponsoring this research project.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".