Experimental study of dynamic bending failure of Laurentian granite: loading rate and pre-load effects
Bibliographic record
Abstract
In deep underground rock engineering projects, rocks are under static pre-load and they may further experience dynamic load due to earthquakes or production blasts. It is thus desirable to consider dynamic failure of rocks subjected to static pre-load. Besides, bending load is commonly encountered near underground openings. Therefore, this study considers the effect of the pre-load on the dynamic bending strength of Laurentian granite (LG). Using a modified split Hopkinson pressure bar system, the semi-circular bend (SCB) method is applied to carry out the bending tests. Five groups of SCB specimens are tested under different pre-loads and loading rates. The results show that under a given pre-load, the flexural tensile strength of LG increases with the loading rate, and decreases with the static pre-load at a given loading rate. The total flexural tensile strength is roughly independent of the pre-load. An empirical equation is used to represent the effects of the loading rate and the pre-load force on the dynamic flexural tensile strength. Furthermore, the flexural tensile strengths measured from SCB tests have higher values than the tensile strengths measured using the Brazilian disc method for the same rock. A nonlocal failure theory is utilized to quantitatively interpret this discrepancy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".