Laboratory investigation into the use of soundless chemical demolitions agents for the breakage of hard rock
Bibliographic record
Abstract
Abstract The method of drilling and blasting with explosives is widely used in rock fragmentation applications in the mining industry for mine development and ore production. However, the use of explosives is associated with rigorous safety and environmental constraints as blasting creates toxic fumes, ground vibrations, and dust. This study is focused on the use of Soundless Chemical Demolition Agents (SCDA) as a more environmentally friendly method for rock breakage and a potential replacement of explosives. In this paper, the results of a series of experimental tests are reported to identify the effect of SCDA on hard rock breakage under no load and under uniaxial loading conditions. Stanstead granite prismatic specimens of 152.4 mm (6ʺ) × 152.4–203.2 mm (6–8ʺ) × 406.4 mm (16ʺ) are used to test the influence of borehole size on the time to fracturing with SCDA borehole size of 25.4 mm (1ʺ), 31.75 mm (1.25ʺ) and 38.1 mm (1.5ʺ). It is shown that the fracturing time decreases with increasing borehole size. It is also shown that specimens subjected to uniaxial compression of 5 MPa fracture as early as 7 h after SCDA mixing. A borehole spacing to borehole diameter ratio of 12.8 to 14.6 is suggested for practical applications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".