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Record W4311816032 · doi:10.1002/srin.202200705

The Causes and Effects of Preannealed Radiative Property Variations Across Full‐Hard Advanced High‐Strength Steel Coils

2022· article· en· W4311816032 on OpenAlexafffund
Nishant S. Narayanan, Kaihsiang Lin, Fatima K. Suleiman, Kyle J. Daun

Bibliographic record

Venuesteel research international · 2022
Typearticle
Languageen
FieldEngineering
TopicSurface Roughness and Optical Measurements
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRadiative transferGalvanizationMaterials scienceWavelengthOpticsScanning electron microscopeSurface (topology)Electromagnetic coilSpectroscopySpectrometerComposite materialGeometryOptoelectronicsPhysicsLayer (electronics)

Abstract

fetched live from OpenAlex

This study investigates the connection between surface topography and radiative property variations across full‐hard (unannealed and cold‐rolled) advanced high‐strength steel (AHSS) coils. Directional–hemispherical reflectivities of samples extracted from various locations on a full‐hard DP‐780 coil are measured using a Fourier transform infrared spectroscopy spectrometer at wavelengths between 0.5 and 20 μm. Surface topography analysis is performed using optical profilometry, optical microscopy, and scanning electron microscopy. Surface height profiles are generated using 3D depth mapping of optical images. The surface profiles are then used in a geometric optical approximation model, which correlates the radiative properties to surface topography variations. Significant differences in radiative properties and surface topography are observed along the length and width of the coil. These variations in radiative properties may explain the temperature excursions that cause nonuniformities in mechanical properties observed across AHSS coils produced on continuous galvanizing lines in the industry.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.325
Teacher spread0.289 · 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 designBench or experimental
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

Citations3
Published2022
Admission routes2
Has abstractyes

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