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Record W3135508098 · doi:10.3390/met11030396

A New Approach to Determine Tensile Stress-Strain Evolution in Semi-Solid State at Near-Solidus Temperature of Aluminum Alloys

2021· article· en· W3135508098 on OpenAlexafffund
Jovid Rakhmonov, Mohamed Qassem, Daniel Larouche, Kun Liu, Mousa Javidani, Josée Colbert, X.-Grant Chen

Bibliographic record

VenueMetals · 2021
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsRio Tinto (Canada)Université LavalUniversité du Québec à Chicoutimi
FundersFonds de recherche du Québec – Nature et technologies
KeywordsSolidusMaterials scienceTearingUltimate tensile strengthStress (linguistics)MetallurgyStrain gaugeDuctility (Earth science)Digital image correlationAlloyComposite materialStrain rateStress–strain curveDeformation (meteorology)Creep

Abstract

fetched live from OpenAlex

Accurate determination of the materials’ strength and ductility in the semi-solid state at near-solidus temperatures is essential, but it remains a challenging task. This study aimed to develop a new method to determine the stress-strain evolution in the semi-solid state of aluminum alloys within the Gleeble 3800 unit. Stress evolution was determined by the newly developed “L-gauge” method, which converted the displacement of the “restrained” jaw, measured using an L-gauge, into the force. This method gives the possibility to determine the flow stress more accurately, especially for the very low stress rang (1–10 MPa) in the semi-solid state at near-solidus temperatures. The digital image correlation technique implemented in the Gleeble unit allowed effective measurement of the heterogeneous strain fields evolving within the specimen under tensile loading. Therefore, the stress-strain curves measured in the semi-solid state help to better understand the alloy’s susceptibility to hot tearing. The results of an AA6111 alloy under different liquid fractions (2.8% at 535 °C and 5.8% at 571 °C) were demonstrated. The reliable stress-strain data and heterogenous strain distribution are beneficial to develop the thermomechanical models and hot-tearing criteria.

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 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 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 score0.072
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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 teacher head, not a consensus.

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

Citations7
Published2021
Admission routes2
Has abstractyes

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