Analysis of energy requirement for hemp fibre decortication using a hammer mill.
Bibliographic record
Abstract
Analysis of energy requirement for hemp fibre decortication using a hammer mill. Canadian Biosystems Engineering/Le gnie des biosystmes au Canada 54: 2.1-2.8. Hemp fibre decortication is an important procedure in hemp fibre processing. The cost of energy during decortication has a direct impact on the commercial value of hemp fibres for industrial products. This study investigated the specific energy requirement for hemp decortication using a hammer mill and the length size distribution of output fibre. Three screen opening sizes (19.28 mm, 25.74 mm, and no-screen scenario) and three feeding masses (200 g, 125 g, and 75 g) were used in hammer mill decortication tests. Test results showed that the 200 g feeding mass and the small screen opening size required the highest specific energy (73.84 J/g). Screen opening size affected the fibre length distribution. For all three feeding mass scenarios, more short fibres were produced when a smaller screen opening was used. Based on the results of analysis using existing Kick's, Rittinger's, and Bond's laws, a linear model was developed to fit the test data in regard to relating specific energy with initial and final fibre lengths. The model performed well for specific energy estimations, especially for the case under 200 g feeding mass. Keywords:
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".