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Record W2279192960 · doi:10.4271/2005-01-0492

Local Strain Measurement in a Strip Cast Automotive Aluminum Alloy Sheet

2005· article· en· W2279192960 on OpenAlexafffund
Jidong Kang, David S. Wilkinson, J.D. Embury, Mukesh Jain

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2005
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsMcMaster University
FundersGeneral Motors of Canada
KeywordsAutomotive industryAlloyAluminiumMaterials scienceMetallurgyStrain (injury)EngineeringAerospace engineering

Abstract

fetched live from OpenAlex

Local strain measurement based on digital image correlation at both macroscopic and microscopic scales is presented. A speckle pattern was used for the macroscopic strain mapping to reveal the inhomogeneous deformation processes occurring during tensile deformation of a strip cast automotive aluminum sheet. Moreover, a novel microscopic strain mapping technique based on scanning electron microscopic (SEM) topography image correlation was introduced for strain mapping down to the grain level. The SEM images taken from an in-situ tensile sample of the same material within a field emission SEM chamber are used to demonstrate the validity of the method. The results clearly reveal the evolution of local strain of order of one as well as the formation of shear band in the material.

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

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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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

Citations6
Published2005
Admission routes2
Has abstractyes

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