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Record W3147771263 · doi:10.1115/1.4050727

A Novel Test Design for Large Strain Uniaxial Reverse Loading of AZ31B Sheet Out of the Rolling Plane

2021· article· en· W3147771263 on OpenAlex
Amir Yazdanmehr, Ali A. Roostaei, Hamid Jahed

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Engineering Materials and Technology · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceFixtureTension (geology)Compression (physics)Magnesium alloyPunchingSheet metalDeformation (meteorology)Shot peeningDeep drawingStructural engineeringForming processesFinite element methodComposite materialShell (structure)Plane stressAlloyMechanical engineeringEngineeringResidual stress

Abstract

fetched live from OpenAlex

Abstract Understanding a magnesium alloy sheet's response to load reversals is important to accurately simulate and optimize a component's manufacturing process. Through this research, the room temperature compression-tension and tension-compression experiments with strains up to ∼12% are performed on AZ31B-H24 sheet specimens along the normal direction of a 6.35 mm-thick sheet. Miniature specimens machined through thickness are tested using a novel setup designed for large strain reverse loading data generation where specimen size is limited. The reliability of the devised setup is verified by finite element simulation and by reproducing in-plane curves obtained via an anti-buckling fixture. A shot peening process involving prevailing through-thickness deformation is modeled and numerical results indicate that employing only in-plane properties of magnesium sheets for simulating such processes can lead to inaccurate predictions.

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.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.018
GPT teacher head0.218
Teacher spread0.200 · 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