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Record W4399057695 · doi:10.1177/03019233231215953

Influence of oxygen enrichment method on the state of blast furnace raceway

2024· article· en· W4399057695 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIronmaking & Steelmaking Processes Products and Applications · 2024
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsWestern University
Fundersnot available
KeywordsRacewayBlast furnaceMetallurgyPig ironOxygenMaterials scienceEngineeringWaste managementForensic engineeringNuclear engineeringChemistryMechanical engineering

Abstract

fetched live from OpenAlex

The numerical simulation is applied to compare the effect of the oxygen enrichment rates under different injection methods on the flow and combustion features. The alteration in the gas velocity follows a congruous pattern for constant air and oxygen enrichment (CAOE) method and the reduced air and oxygen enrichment (RAOE) method. The oxygen enrichment rate increases by 1% and the velocity at the tuyere increases by 2.92 and 0.78 m s −1 . The CAOE method has a more significant influence on the temperature and burnout of coal particles than that of the RAOE method. Furthermore, the burnout of coal particles at the exit of the raceway is 79.45% and 78.95%, at an oxygen enrichment rate of 12% under the conditions of the CAOE method and RAOE method. To improve the penetration capacity of the hearth and achieve higher burnout of pulverised coal, the CAOE method is recommended to enrich oxygen.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.257
Teacher spread0.246 · 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