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Record W2080863251 · doi:10.1179/174329009x409723

Effects of cold and hot densification on the mechanical properties of a 7XXX series powder metallurgy alloy

2009· article· en· W2080863251 on OpenAlex

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

VenuePowder Metallurgy · 2009
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsDalhousie University
FundersAUTO21 Network of Centres of ExcellenceNatural Sciences and Engineering Research Council of Canada
KeywordsSwagingMaterials scienceAlloyUltimate tensile strengthMetallurgyPowder metallurgyHot workingMicrostructure

Abstract

fetched live from OpenAlex

The objective of this work was to investigate the effects of hot and cold swaging on the density and mechanical properties of a commercial Al–Zn–Mg–Cu powder metallurgy alloy known as Alumix 431D. To do so, as sintered samples of the PM alloy were swaged under a variety of conditions and characterised. For comparison purposes, equivalent characterisation tests were completed on the chemically similar wrought alloy 7075-T6. Cold swaging was moderately successful provided the as sintered billets were annealed or solutionised before densification. Here, modest improvements in density and tensile properties were noted. Hot swaging proved to be a more effective approach. Optimal properties were achieved when samples were preheated to 470 ± 10°C. When processed in this manner, a density of 99·6% of theoretical was realised while the tensile and fatigue properties exceeded those of the wrought 7075-T6 alloy tested for comparison purposes.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.011
GPT teacher head0.182
Teacher spread0.171 · 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