The Influence of Explosive and Rock Mass Properties on Blast Damage in a Single-Hole Blasting
Bibliographic record
Abstract
In rock blasting for mining production, stress waves play a major role in rock fracturing, along with explosive gases. Better energy distribution improves fragmentation and safety, lowers production costs, increases productivity, and controls ore losses and dilution. Blast outcomes vary significantly depending on the choice of the explosive and the properties of the rock mass encountered. This study analyzes the effects of rock mass and explosive properties on blast outcomes via numerical simulation using data from the case study, and later validates the simulation results from the field blast fragmentation. The findings suggest that, for a given set of rock properties, the choice of explosive has a major influence on the resulting fragmentation. Strong explosives (high VOD and detonation pressure) favor large fracture extents in hard rocks, while weaker explosives offer a better distribution of explosive energy and fractures. The presence of rock structures such as rock contacts and joints influences the propagation of stress waves and fractures depending on the structures’ material properties, the intensity and orientations, and the direction and strength of the stress wave. When the stress wave encounters a contact depending on its direction, it is enhanced when traveling from soft to hard and attenuates in the opposite direction. The ability of the stress wave to cause fracturing on the opposite side of the contact depends on the intensity of the transmitted wave and the strength of the rock. Transmitted wave intensity is a function of the strength of the incident wave and the impedance difference between the interface materials. The presence of joints in the rock mass affects the propagation of the stress wave, mainly depending on the infill material properties and the angle at which the stress wave approaches the joint. Less compressible, higher stiffness joints transmit more energy. More energy is also transmitted in the areas where the stress wave hits the joint perpendicularly. Joints parallel to the free face offer additional fracturing on the opposite side of the joint. Other parameters, such as the joint width, continuity, fracture frequency, and the distance from the charge, enhance the effects. To achieve effective fragmentation, the blast design should mitigate the effect of variability in the rock mass via explosive selection and pattern design to ensure adequate energy distribution within the limits of geometric design.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".