THE EFFECT OF MICROWAVE IRRADIATION ON THE MECHANICAL PROPERTIES OF KIMBERLITE AND LIMESTONE
Bibliographic record
Abstract
THE EFFECT OF MICROWAVE IRRADIATION ON THE MECHANICAL PROPERTIES OF KIMBERLITE AND LIMESTONE Abstract In underground excavation, rock fragmentation can be achieved by blasting with explosive materials or using continuous excavation machinery. The significant challenges with the explosives include noise, vibration, pollution, and potential issues such as damage to nearby structures. A less disruptive method for breaking rocks is using machines such as tunnel boring machine and road header those have the capability of continuous operation and are suitable for autonomous mining. In hard rock applications, the excavation machinery is associated with high equipment wear rates, low penetration rates and consequently high operating costs. This paper investigates the work being undertaken at McGill University on the effect of microwave (MW) irradiation on hard rocks to facilitate continuous mining and improve the production rate while reducing costs. Tuffistic Kimberlite (TK) and limestone rocks were studied in this research. Physical properties of untreated samples were measured, and the rock samples were treated for various exposure times in a multi-mode MW unit at power levels ranging from 2 to 10 kW. The results indicate that MW irradiation reduced the strength of TK and limestone rocks. It was concluded that Brazilian Tensile Strength (BTS) and Uniaxial Compressive Strength (UCS) of samples decayed proportionally with exposure time and power level. Keywords: Kimberlite, Microwave Irradiation, Fragmentation, Mechanical Strength, Rock Excavation
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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 | 0.000 |
| 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".