Bibliographic record
Abstract
A common set of reactions, given in Table 15.1, occurs when carbonaceous solids undergo thermal processing. Whether the aim is pyrolysis, gasification, or combustion, each of these reactions occurs in some parts of the reactor because of gas–solids contacting. In this chapter, we consider, in order, gasification as an endothermic process to generate H 2 and CO mixtures for fuel or synthesis gas, pyrolysis as a process to generate useful tars (or liquids), and combustion as a process to produce heat. Gasification background Most commercial gasifiers use coal as feed, and may be classified by the type of solids–gas contacting (moving, entrained, fluidized, or spouted bed), by the state of the ash (dry, agglomerated, or molten), and by the oxidant (air, air–steam, or oxygen–steam). A low-calorific-value gas results from air–steam gasification, and a medium-calorific-value gas from using steam or steam–oxygen mixtures. The carbonaceous feedstock may be fed as a dry solid, a sludge, or a slurry. Performance measures can be identified for comparing gasifiers of different designs and operating conditions. For production of fuel gases, the heating value of the produced gas is important and is usually reported on a dry gas basis. For synthesis gas or pure hydrogen production, the molar ratio of H 2 ∕CO leaving the gasifier is critical. Low tar yields are usually beneficial, unless a raw fuel gas is desired. For sizing scaled-up gasification processes, throughput of solids feed per unit cross-section of reactor (kg/m 2 s) is of major importance.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.013 |
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".