A Study of Particle Size Effect on Biomass Torrefaction and Densification
Bibliographic record
Abstract
The particle size effect on torrefaction of pine particles and formation of torrefied pellets has been studied in a thermogravimetric analyzer (TGA) and a tubular fixed bed reactor. The fixed bed reactor was also used to produce torrefied samples for a single-die press unit for the densification test. Both the TGA and fixed bed reactor torrefaction test results showed that the torrefaction rate was affected by the particle size, especially at high temperatures. Although the temperature gradient inside particles smaller than 1 mm is very small during torrefaction, the internal diffusion of generated vapors inside particles imposes an impact on the global torrefaction reaction rate. The hard core or nonshrinkage particle model with a first order torrefaction reaction can predict the reaction data reasonably well, with the data-fitted effective vapor diffusivity coefficient. The densification tests showed that more energy was required to make pellets from larger torrefied particles, while the water uptake and Meyer hardness tests of pellets revealed that good quality torrefied pellets could be obtained from fine torrefied sawdust particles.
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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 | 0.001 |
| 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) | 0.001 | 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".