High velocity impact fragmentation and the energy efficiency of comminution
Bibliographic record
Abstract
Comminution processes are essential stages in mining and mineral processing operations to reduce the size of ore and rock, and liberate the valuable mineral for beneficiation. Comminution is energy-intensive and responsible for the majority used during mineral recovery. Energy use is inherently inefficient with almost all being dissipated as heat instead of new surface area (energy). Typical grinding efficiencies in terms of new surface area created range from 1 to 2 percent with crushing efficiencies lying slightly higher at 3 to 4 percent. High-pressure rolls and roller crushers are reported to operate at levels as high as 7 to 8 percent, while blasting has the highest efficiency of all ranging from 13 to 20 percent. This thesis reports on studies conducted into the effect of high strain rate achieved through high velocity impacts to enhance energy efficiency and mineral liberation. The research is focused on understanding the fracture mechanics of comminution at ultra-high strain rates and quantifies the distribution of energy with respect to generating new surface area. In interpreting breakage phenomena, accurate measurement of surface roughness and surface area is essential. A novel approach to determine these parameters based on fractal analysis has been developed. Changes in surface roughness of broken specimens under variable loading rates were studied using a laser probe to generate 3D topographical maps of the fracture surfaces. The results indicate that surface roughness and hence, specific particle size decreases to ~1 micron. Below this limit, surface.roughness begins to diminish from, particle-particle attrition. The influences of particle shape, porosity, and size have been accounted for in this analysis. An apparatus to measure the quantitative parameters of high velocity impact on aggregated rock samples has been developed. Experiments have been carried out on three materials at projectile velocities up to 450 ms⁻¹ utilizing a compressed air gas gun. The results, suggest energy efficiency of rock breakage can be improved by as much as 2 to 3 times under high velocity impact for the same energy input level. The effect is subtle and sensitive to the impact zone dimension, the hardness and porosity of the material, and the constraining or not of the sample. Our research aims to develop better understanding of the fundamentals of fragmentation with the purpose to increase efficiency and find ways to reduce the energy required for comminution. surface area, increases with increasing loading rate by several orders of magnitude as
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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 | 0.000 | 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) | 0.000 | 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".