MétaCan
Menu
Back to cohort
Record W4376288159 · doi:10.18280/rcma.330202

Analysis of the Joint Effect of Heat Treatments and Stress Ratio on the Growth Behavior of Fatigue Cracks in Cast Aluminum Alloys under Combined Loading (Bending-Torsion)

2023· article· en· W4376288159 on OpenAlexvenueno aff
Mustafa Sami Abdullatef, Anees Al-Tamimi, Faten N. Alzubaidi, Yasser Ahmed Mahmood

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2023
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceTorsion (gastropod)Paris' lawMetallurgyAluminiumComposite materialStructural engineeringBendingCrack closureFracture mechanicsEngineeringMedicine

Abstract

fetched live from OpenAlex

The behavior of microstructural short fatigue cracks (20-100 µm in length on the same scale as the grain size) in the cast aluminum alloy A07710-T6 was investigated.Two heat treatment conditions have been used, an underaged and an overaged microstructure, chosen to have very similar tensile properties, so that the effects of precipitation and hence slip distribution on fatigue behavior could be studied at the same strength level.The results of short crack propagation tests performed on smooth specimens at 25℃ and R=0.1 are compared to conventional (long) fatigue crack propagation and threshold results under the same conditions.The short crack data is also compared to long crack tests conducted at constant maximum applied load (so that the R-ratio increases to a value above 0.8 as the threshold is approached).In conventional long crack tests, better low and high threshold crack propagation resistance is associated with the underaged microstructure.This behavior is also reflected in the thresholds obtained at high R.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.042
GPT teacher head0.259
Teacher spread0.217 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207