MétaCan
Menu
Back to cohort
Record W4416626491 · doi:10.4028/p-rod8wm

Experimental Investigation of Gas-Oscillation Superplastic Forming of AA5083 Aluminum Sheet in a Dual-Cavity Tool

2025· article· W4416626491 on OpenAlex
Eugene Ryzer, Song Yang, Shuyan Xu, Leo Kiawi, Daniel E. Green, G. W. Rankin

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.

Bibliographic record

VenueKey engineering materials · 2025
Typearticle
Language
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSuperplasticityFormabilityUltimate tensile strengthAluminiumGrain Boundary SlidingAlloyForming processesProcess (computing)

Abstract

fetched live from OpenAlex

Experimental studies show the significant improvement of superplastic formability of AA5083 alloy under oscillating loads. Tensile tests are performed to determine the benefits of oscillatory stress at 450°C. Microstructural analysis of the tested specimen indicates an improvement in the grain boundary sliding mechanism with oscillation. Based on the knowledge from the tensile tests, a Gas-Oscillation Superplastic Forming (GO-SPF) process is developed. The cycle time of the GO-SPF process to form a AA5083 part in a dual-cavity tool without failure is impressively 4.5 times shorter than the required one of a conventional superplastic forming (SPF) process, while the GO-SPF process is found to provide practically identical forming quality to the conventional SPF process. Significant potential benefits of the GO-SPF process are presented.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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