An exploratory study of explosion potential of dust from torrefied biomass
Bibliographic record
Abstract
Torrefaction makes biomass brittle, and as such it is likely to produce more dusts during handling and transportation. So, it could increase the risk of explosion in plant using torrefied biomass. As the torrefaction technology enters commercial market the safety aspect of torrefied wood becomes important. The present paper is one of the first examinations of the question if torrefaction makes the biomass dust more explosive. Effects of torrefaction conditions on two important parameters that define the explosivity of a dust, i.e., minimum ignition temperature (MIT) and minimum explosible concentration (MEC) were studied. Above parameters were measured for Poplar wood before and after torrefaction. Three different particle size distributions of the wood, torrefied at 200, 250 and 300 °C, were tested. Exploratory experiments reported here found negligible effect of torrefaction on measured values of;Deg;ME;Deg;C and MIT of biomass. However, torrefied particles larger than 100 micron showed higher values of MIT than that for raw biomass.
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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 | 0.000 |
| 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".