Application of Soundless Chemical Demolition Agents to Cold Climate Conditions: An Environmentally Sustainable Approach to Rock Breakage
Bibliographic record
Abstract
Soundless Chemical Demolition Agents (SCDA) are powdery cementitious substances that, when combined with quicklime (CaO), produce a substantial increase in volume due to chemical reactions and expansive pressure. SCDA has been commonly employed in civil engineering to demolish concrete foundations when the use of explosives is prohibited or restricted. However, the potential application of SCDA in mining, specifically for breaking oversized boulders under sub-zero Celsius conditions remains relatively unexplored. This study aims to investigate the effectiveness of SCDA as an environmentally friendly alternative to secondary blasting in cold climate conditions. Laboratory tests were conducted using concrete and granite blocks with varying borehole size and length and cold ambient temperatures, as SCDA efficiency tends to decrease in low-temperature environment. All tests were conducted in the Rockbolting Laboratory of the McGill Mine Design Lab. The evaluation of test results focuses on three methods: Time to Critical Strain (TCS), Time to First Crack (TFC), and Minimum Demolition Time (MDT). The results of laboratory tests are in line with previous research and provided insights into cold temperature applications of SCDA. In addition, to identify the tensile strength of the granite blocks, Brazilian Tensile Strength tests were conducted.To overcome the drawback on the effectiveness of SCDA caused by cold temperature, a novel approach using high-temperature wire, utilizing nichrome wire, and electrical DC current was tested to expedite the reaction process in concrete and granite blocks with different borehole diameters, ambient temperatures, and voltage combinations. The application of the high-temperature wire method proved to be highly effective in reducing the TCS, TFC, and MDT values under cold ambient temperatures.Furthermore, the study incorporates steady state 2D heat transfer modeling to investigate the heat transfer process induced by the high-temperature wire into the host block and the SCDA. To accomplish this task, ABAQUS finite element modelling software was used. Numerical model results were then compared with the experimental data in steady state conditions, i.e., after the SCDA has fully cured and the effect of DC current has stabilized. The temperature readings obtained from numerical modelling and the laboratory tests appear to be in good agreement. A number of suggestions for future research are made including 3D heat transfer modelling and the application to real life boulders in surface mining operations
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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 | 0.000 |
| 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) | 0.001 | 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".