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Record W4255309909 · doi:10.32920/ryerson.14660985.v1

Cyclic deformation behavior of an automotive material

2021· preprint· en· W4255309909 on OpenAlexaff
Amir Reza Emami

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceDimpleUltimate tensile strengthEutectic systemStrain hardening exponentAlloyComposite materialMicrostructureHardening (computing)AcicularFractographyFracture (geology)Deformation (meteorology)Metallurgy

Abstract

fetched live from OpenAlex

The A356 Al-Si-Mg cast alloy is being used in the automotive industry to replace some heavy components due to its fabrication flexibility and high strength-to-weight ratio. This study was aimed at identifying cyclic deformation characteristics and fracture mechanisms of the A356 alloy in different material conditions. The microstructure consisted of primary a-Al matrix and eutectic regions containing Si particles of acicular (T5) and spherical (T6 and ModT6) morphologies. The ModT6 sample had a higher yield strength (YS) and ultimate tensile strength (UTS) but a lower strain hardening exponent than the T6 sample, while the T5 sample had a lower YS UTS but a higher initial strain hardening than the T6 sample. The T6 sample exhibited a higher cyclic hardening capacity and longer fatigue life. Crack initiation in both tensile and fatigue tests occurred at the sub-surface voids. Quasi-cleavage fracture characteristics in the T5 condition and dimple-like fracture features in the T6 and ModT6 were observed.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same topicAluminum Alloys Composites PropertiesFrench-language works237,207