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Modeling Transient Jet Impingement Cooling of Moving Hot Steel Plates

2022· article· en· W4308988003 on OpenAlexaff
Gilles Guedia Guemo, Amir Hossein Nobari, Vladan Prodanovic, Matthias Militzer

Bibliographic record

VenueISIJ International · 2022
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNozzleSTRIPSWater coolingMaterials scienceMechanical engineeringTransient (computer programming)Jet (fluid)Structural engineeringEngineeringComposite materialComputer scienceAerospace engineering

Abstract

fetched live from OpenAlex

Accelerated cooling (ACC) is one of the key processing steps in the production of Advanced High Performance Steels. In order to obtain thermo-mechanically controlled processed (TMCP) steel products with desired microstructures and mechanical properties, it is necessary to properly adjust the processing parameters of the cooling facility, and therefore it is critically important to quantify the physical process of heat removal by applying water jets on the hot surface of steel. In the present study we propose a mechanistic model for top jet cooling of a moving plate with circular and planar nozzles. The simulation model has been developed based on the extensive experimental database generated with pilot scale runout table tests, and it provides a potentially powerful tool for simulation of cooling of steel strips and plates over the entire length of the cooling facility.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.229
Teacher spread0.210 · 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 designSimulation or modeling
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

Citations12
Published2022
Admission routes1
Has abstractyes

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