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Property Anisotropy in Magnesium Containing Aluminium Alloys

2000· article· en· W2129538397 on OpenAlexaff
C. H. Johnson, David J. Lloyd

Bibliographic record

VenueMaterials science forum · 2000
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsMaterials scienceAnisotropyUltimate tensile strengthWork hardeningElongationMetallurgyStrain hardening exponentDuctility (Earth science)AluminiumHardening (computing)Texture (cosmology)Composite materialMicrostructureOptics

Abstract

fetched live from OpenAlex

Property anisotropy has been investigated in a range of both model and commercial 5xxx series Al-Mg alloys, in the annealed temper. The term property anisotropy includes the whole range of mechanical tensile properties, but in this paper we are particularly concerned with anisotropy in the tensile elongation to fracture. The tensile elongation in these alloys typically achieves a maximum value in the 45° direction to the rolling direction, and a minimum when the sheet is deformed in a direction parallel to the rolling direction. Both microstructural anisotropy and crystallographic texture have been considered in analysing the results. It is shown that microstructural anisotropy and global parameters, such as the work hardening exponent, n, and the plastic strain ratio, r-value, cannot explain the ductility anisotropy. However, the anisotropy can be understood in terms of the influence of crystallographic texture on the work hardening rate. The behaviour of the work hardening rate with stress and strain controls the onset of plastic instability, and subsequent 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 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)0.001
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.010
GPT teacher head0.235
Teacher spread0.224 · 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

Citations6
Published2000
Admission routes1
Has abstractyes

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