Comparative Study of the Rosin-Rammler and Gates-Gaudin-Schuhmann Particle Size Distribution Models for Microwave-Assisted Crushing Analysis
Bibliographic record
Abstract
Microwaves selectively heat dielectric minerals within the ore particles during a relatively brief exposure period, inducing thermal stresses that generate cracks, thereby diminishing the structural integrity of the ore particles. The immediate effect of employing this technique is an alteration in the particle size distribution (PSD) of the comminution product. In this research, two types of diamond-bearing kimberlite ore underwent microwave irradiation before the crushing process. The microwave experimentation was carried out utilizing a multi-variable power system with a maximum capacity of 15 kW, within a single-mode cavity structure. The exposure time was adjustable to vary the input microwave energy, which ranged from 6 kJ to 270 kJ. Three distinct narrow feed size classes were examined: -31.5 +16 mm, -16 +6.7 mm, and -31.5 +6.7 mm. Each sample weighed five hundred grams. Both the microwave-treated samples and the untreated samples (as-received) were subjected to crushing using a single-roll crusher. The PSD of the crushed product was determined through a standard sieving test and subsequently analyzed using empirical PSD models. These models are advantageous for enhancing the accuracy of PSD analysis by linearizing datasets that often exhibit skewness towards the distribution's tail end. Two widely recognized empirical PSD models, the Rosin-Rammler (RR) and Gates-Gaudin-Schuhmann (GGS) models, were employed to assess how microwave pre-treatment influences the PSD of the crushed product. Various comparative parameters derived from these models, such as the P50, distribution uniformity (DP), and critical fine sizes, were evaluated for both untreated crushed samples and the samples treated with microwaves. The findings indicated that crushed products treated with microwaves generally displayed improved alignment with both PSD models in comparison to the untreated samples. Notably, the GGS model exhibited marginally higher overall r-squared values compared to the RR model. Moreover, the microwave-treated samples showcased a slightly coarser and more uniform PSD when contrasted with the untreated counterparts. Among the various microwave energy inputs tested, the lowest input at the highest power level yielded the most substantial increments in P 50 and DP. Simultaneously, it led to the most significant reduction in fractions corresponding to critical fine sizes.
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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".