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Record W2802565708 · doi:10.1177/0021998318770505

Experimental investigation and phenomenological modeling of hygrothermal effect on tensile fatigue behavior of carbon/epoxy plain weave laminates

2018· article· en· W2802565708 on OpenAlexaff
Mohamed Khay, AD Ngo, Rajamohan Ganesan

Bibliographic record

VenueJournal of Composite Materials · 2018
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsConcordia UniversityÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceComposite materialUltimate tensile strengthEpoxyStiffnessDelamination (geology)Tension (geology)ModulusResidual strengthComposite laminatesPlain weaveMoistureStress (linguistics)Composite number

Abstract

fetched live from OpenAlex

The purpose of this paper is to study the hygrothermal effect on fatigue behavior of quasi-isotropic carbon/epoxy plain weave aerospace laminates containing artificial flaw under axial tension–tension loading. Dry and wet specimens were tested at tensile load-controlled cyclic loading with a stress ratio R = 0.1 and a load frequency of 7 Hz at room temperature (RT) and at 82℃ under different stress levels. Allowable stiffness change as a failure criterion was used to determine the delamination propagation onset threshold under cyclic tensile loading at each environmental condition. The delamination propagation onset was verified using the ultrasonic imaging (C-Scan) technique. The experimental results show that (1) fatigue life of CFRP specimens was more individually affected by moisture than by temperature and (2) combined moisture and temperature cause a drastic decrease in fatigue life. Finally, an investigation of the effect of hygrothermal conditions on stiffness degradation and damage of composite laminates subjected to tensile fatigue loading has been also carried. On the basis of the residual stiffness degradation, a damage variable was presented and phenomenological damage models were proposed by employing fatigue modulus and secant modulus concepts as measure of material damage.

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 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 score0.007
Threshold uncertainty score0.639

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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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.

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
Published2018
Admission routes1
Has abstractyes

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