MétaCan
Menu
Back to cohort
Record W4389584776 · doi:10.17118/11143/21003

Influence of axial fan casing flow on temperature uniformity during theheat treatment process of large-size forgings in an industrial size electricfurnace

2023· article· en· W4389584776 on OpenAlexaff
Sajad Mirzaei, Farzad Bazdidi–Tehrani, Abdelhalim Loucif, Jean-Benoît Morin, Mohammad Jahazi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsCégep de Sorel-TracyÉcole de Technologie Supérieure
Fundersnot available
KeywordsCasingForgingMaterials scienceGrain sizeFlow (mathematics)Mechanical engineeringProcess (computing)Axial compressorComposite materialMetallurgyEngineeringMechanicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

The effect of changes in the structure of the axial fans mounted on the ceiling of an industrial size electric heat treatment furnace on temperature uniformity during the tempering process of large-size steel forgings was investigated.Variable mechanical properties or microstructures could be obtained if the temperature distribution through the volume of the large size bloc is not uniform during the heating process.Therefore, it is important to study the influence of different variables on the temperature evolution during the heat treatment process.Such study will also result in increasing the energy efficiency of the furnace.Due to the difficulty of directly measuring internal velocities and temperature fields in furnaces, the numerical approach can facilitate the identification of the principal phenomena that govern thermal and fluid behavior within the furnace and could be helpful in improving furnace operation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicMetallurgical Processes and ThermodynamicsFrench-language works237,207