Evaluation of compaction equations applied to four biomass species
Bibliographic record
Abstract
Mani, S., Tabil, L.G. and Sokhansanj, S. 2004. Evaluation of compaction equations applied to four biomass species. Canadian Biosystems Engineering/Le genie des biosystemes au Canada 46: 3.553.61. The compression behavior and compaction mechanism of wheat and barley straws, corn stover, and switchgrass grinds were investigated using three compaction equations viz. Heckel, CooperEaton, and Kawakita-Ludde models. Compression tests of biomass samples were conducted at different applied forces, moisture contents, and particle sizes using the single pelleter-Instron tester. For each test, the pressure-density data were collected to characterize the compression behavior of biomass grinds. Among the four biomass grinds studied, corn stover grind reached its maximum density at low pressure, whereas the other biomass grinds required high pressure to reach maximum density. The compression data were fitted to three compaction models for explaining the compaction mechanisms. Among the three models, the Kawakita-Ludde and Cooper-Eaton models fitted well with the pressure-density data for all biomass grind samples. The Cooper-Eaton model parameters showed that the dominant compaction mechanisms for biomass grinds were rearrangement of particles followed by elastic and plastic deformation and that mechanical interlocking was negligible. From the KawakitaLudde model, it was found that compacts prepared from switchgrass grind had higher yield strength than compacts made from other biomass grinds. Lower yield strength was predicted by the KawakitaLudde model for compacts from corn stover grind.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".