Thermogravimetric Analysis and Combustion Performance of 10 Common Types of Tree Leaves in Maoer Mountain Region
Bibliographic record
Abstract
By thermogravimetric analysis method,this paper studied pyrolysis characteristics and kinetics of 10 kinds of representative trees species grown in Maoer Mountain of Heilongjiang Province. Besides,it analyzed basic pyrolysis process of fuel using TG-DTG curve. Through pyrolysis parameters,it made quantitative comparison of pyrolysis characteristics of the different plant fuel and obtained the relation between lignin,hemicellulose and cellulose. By grading reaction kinetics model( Coats-Redfem method),it obtained their activation energy E and frequency factor A. All samples of pyrolysis in nitrogen atmosphere underwent three major stages,namely,water precipitation,fast pyrolysis and carbonization. In addition,Mongolian scotch pine and Black pinus tabulaeformis carr have better fireproof performance than other leaves with ignition temperature of 275. 17 ℃ and 274. 38 ℃ and activation energy of 44. 188 6 KJ / mol and 42. 864 3 KJ / mol respectively. Further,with the aid of the technology of relative limited oxygen index( LOI),it measured the LOI of fuel. Its numerical value can reflect the fuel combustibility. Oxygen index of elm is 26. 4% and belongs to flame resistant level,while black pinus tabulaeformis oxygen index is 20. 2% and belongs to inflammables.
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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 | 0.001 | 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) | 0.000 | 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".