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The Development of a High Strain Rate Superplastic Al-Mg-Zr Alloy

2001· article· en· W2071691659 on OpenAlexaff
Richard Dashwood, Roger Grimes, Andrew Harrison, H. M. Flower

Bibliographic record

VenueMaterials science forum · 2001
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsKensington Health
Fundersnot available
KeywordsSuperplasticityMaterials scienceAlloyMetallurgyStrain rateStrain (injury)Internal medicine

Abstract

fetched live from OpenAlex

In order for superplastic forming of aluminium to break out of the niche market low cost alloys are required that exhibit higher strain rate capability that are capable of volume production. This paper describes an investigation into the feasibility of producing such an alloy. A series of Al-4Mg alloys with 0, 0.25, 0.5, 0.75 & 1% Zr additions was prepared using a cheap particulate casting route, in an attempt to achieve higher levels of Zr supersaturation than are possible with conventional casting. The particulate was processed into a sheet product via hot extrusion followed by cold rolling and the effect of a number of process variables on the SPF performance of the sheet was investigated. It was found that increasing the Zr content, and manipulation of the thermomechanical processing conditions improved the SPF performance. Ductilities in excess of 600% have been achieved at a strain rate of 0.01 s-1, together with flow stresses less than 15MPa.

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 score0.002

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 science0.0010.000
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 head0.209
Teacher spread0.198 · 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

Citations11
Published2001
Admission routes1
Has abstractyes

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