Effect of mixing water temperature on the mechanical performance of soundless chemical demolition agents for rock breakage
Bibliographic record
Abstract
Rock fragmentation in hard rock mining has traditionally relied on explosives which raises significant environmental and safety concerns for both workers and local communities. In response, soundless chemical demolition agents (SCDAs) primarily composed of lime (CaO), offer safer and more sustainable alternative to traditional blasting due to their soundless, vibrationless, and fumeless properties. This study is focused on examining the effect of mixing water temperature on the rock breakage performance of two commercially available SCDA brands, namely Betonamit type R (BT-R) and Dexpan type 3 (DXP-3). The experiments were conducted using 15 cm cubic granite rock specimens as the host material under various ambient temperatures. The study revealed an increase in mixing water temperature significantly accelerates the mechanical performance of SCDAs, particularly in cold ambient conditions. For instance, increasing the mixing water temperature from 20°C to 40°C reduced the time to first crack (TFC) by 36 % for BT-R and 74 % for DXP-3 under an ambient temperature of 0°C. A corresponding reduction in minimum demolition time (MDT) was also observed. At higher ambient temperatures, the impact of mixing water temperature was found to be less pronounced for both SCDA types. It is concluded that high mixing water temperature would be highly recommended for cold climate applications in both open pit and underground mining.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".