Effects of Metallic Heating Plates on Coal Pyrolysis Behavior in a Fixed-Bed Reactor Enhanced with Internals
Bibliographic record
Abstract
A newly configured fixed-bed reactor with internals has been proposed to enhance the coal pyrolysis performance. In this study, the effects of metallic plates on coal pyrolysis behavior were investigated in this reactor. The results show that the increased quantity of the metallic plates enhanced the heat transfer and shortened the residence time of volatiles within the coal particles. In addition, the pressure drop results suggest that the increased quantity of plates caused short circuiting of gas and raised the particle interstices, which reduced the gas diffusion resistance of pyrolysis products. Therefore, more gaseous pyrolysis products flowed into central low-temperature coal bed and escaped from the gas collection pipe, suppressing the secondary reaction of pyrolysis products and increasing the tar yield and quality. At a furnace temperature of 900 °C, the increase in metallic plates from 0 to 8 raised the tar yield and light tar fraction from 5.20 and 69.5 wt % to 7.86 and 77.0 wt %, respectively. Meanwhile, the ≤C 14 hydrocarbons were elevated from 42.11 to 50.44 wt %, but the ≥C 20 hydrocarbons were lowered from 29.95 to 19.74 wt %. However, an excessive increase in plates raised the heating rate of coal, cracking more pyrolysis products and decreasing the tar yield and quality.
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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) | 0.001 | 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 | 0.001 | 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".