Laboratory investigation into soundless chemical demolition agents for rock breakage in underground mines
Bibliographic record
Abstract
The method of drilling and blasting with explosives is widely used 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. The following study is conducted on Soundless, Explosive-Free Chemical Demolition Agents (SCDAs), a more environmentally friendly method for the fragmentation of rock as a potential replacement of explosives. SCDAs are powdery materials similar to Portland cement, which when mixed as a slurry and poured into blind drilled holes, an expansive pressure is produced upon curing and eventually breaks the material apart. Given that SCDAs are commercially available, there is proof of workability in civil engineering applications for the breakage of concrete foundations. SCDAs are commonly used in the demolition of concrete foundations as well as in stone quarries where the use of explosives is either restricted or prohibited. An interest is drawn towards SCDAs due to its environmental advantages which mitigate the risk of explosives. This study is a step in investigating its workability in hard rock mine development and production where the rock is subjected to high in-situ confinement pressure which would make rock breakage cumbersome. A drawback of the SCDAs is that the time needed to develop the full expansive pressure is too long for practical mine development applications. The primary goal of the study is to accelerate the expansion rate of SCDAs as one of the steps towards development of a feasible method of rock breakage in underground mines. The SCDA used in this investigation is Betonamit, a commercially available expansive cement. The experimental investigation was conducted in the Rockbolting Lab of the Mine Design Laboratory. This study is an extension of the work previously conducted by Musunnuri & Mitri (2009) and Dessouki & Mitri (2011) in the Mine Design Laboratory of McGill University.The factors investigated are: the expansive pressure, expansive pressure rate, and fractural growth on concrete blocks. The effect of chemical additives on expansive pressure is investigated with the goal to reduce the time of expansion. Common concrete accelerators including calcium chloride, sodium chloride, calcium formate, and sodium were investigated.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".