Quantifying particle breakage through a shape factor of the particle size distribution
Bibliographic record
Abstract
Quantifying the process of particle breakage is essential whenever a macroscopic investigation into the phenomenon is addressed. Some authors relate an indicator of the evolution of particle breakage, usually the surface created, to a measure of the mechanical loading. Others refer to the evolution of the particle size distribution (PSD) to better understand the problem. In this study, a shape factor of the PSD curve is used as a breakage parameter. The slope of the linear trendline of the PSD in a log-log plot was found to be reasonably representative of the shape of the PSD, for engineering granular materials. It was shown that the new breakage parameter is adapted to both well graded and uniformly graded materials, but cannot be used to describe gap-graded soils. This parameter is first studied from a micromechanical point of view, before being compared to three widely used breakage parameters: Hardin, Marsal and Einav’s breakage parameters. The transition between these three parameters and the proposed parameter is provided. The main objective of this study is to allow the operation and utilisation of experimental results, which are reported in the literature through one of the available breakage parameters, or through PSD plots.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".