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Record W2008687637 · doi:10.1520/jai12763

The Use of Digital Image Correlation to Verify the Behavior of Fiber Metal Laminate Cylinders under Torsional Loading

2006· article· en· W2008687637 on OpenAlexaff
David Bäckman, A Jodoin, C. Poon, Y Mendis

Bibliographic record

VenueJournal of ASTM International · 2006
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsDigital image correlationMaterials scienceComposite materialFiberStructural engineeringMetalEngineeringMetallurgy

Abstract

fetched live from OpenAlex

Abstract Measurements made using digital image correlation were compared to both strain gages and displacement transducers during the testing of a fiber metal laminate cylinder under torsional loading. The image correlation results showed very good agreement with measurements made using both strain gages and displacement transducers. The image correlation results were also used to measure out-of-plane displacement of the cylinder and to determine the exact onset of initial buckling. Although strain gages remain a proven and valuable technology for measuring strain, image correlation can completely characterize full-field strains and full-field displacements in the cylinder. In addition, image correlation is able to provide insight into the material behavior at strain values where the gages are less reliable and more prone to failure.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.044
GPT teacher head0.281
Teacher spread0.237 · 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 teacher head, 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

Citations2
Published2006
Admission routes1
Has abstractyes

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