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Record W1893414359 · doi:10.1017/cbo9780511777936.016

Gasification, pyrolysis, and combustion

2010· book-chapter· en· W1893414359 on OpenAlexaff
A. P. Watkinson, Antônio Carlos Luz Lisbôa

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook-chapter
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPyrolysisCombustionEndothermic processProcess (computing)Waste managementChemical engineeringMaterials scienceChemistryOrganic chemistryAdsorptionEngineeringComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.013

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.

Opus teacher head0.010
GPT teacher head0.166
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations8
Published2010
Admission routes1
Has abstractyes

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