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Record W4387457517 · doi:10.1177/14644207231205600

Efficient accelerated assessment of fatigue life in Kevlar, Flax, and Kevlar/Flax hybrid composites

2023· article· en· W4387457517 on OpenAlexaff
Ahmed Sarwar, Habiba Bougherara, D. C. D. Oguamanam

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications · 2023
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsKevlarComposite materialEpoxyMaterials scienceDissipationAramidWaxTension (geology)Composite numberUltimate tensile strengthFiber

Abstract

fetched live from OpenAlex

This paper presents experimental investigations on the fatigue behavior of Flax, Kevlar, and Kevlar/Flax-reinforced epoxy specimens under accelerated step loading. The samples consisted of a 12-ply-Flax core in a sandwich structure surrounded by a two-layer Kevlar skin, and they were tested under tension–tension progressive cyclic loading. The fatigue strength of the hybrid and its constituents were predicted using thermography and energy dissipation methods with a reduced amount of testing. The results for the Flax/epoxy, Kevlar/epoxy, and Kevlar/Flax/epoxy composites showed similar plateauing for both temperature and energy dissipation at around 6000 cycles. It was observed that Flax, Kevlar, and their hybrid exhibited bilinear behavior based on the stabilized temperature and stabilized dissipated energy over the tested stress levels with the fatigue strength of 47%, 53%, and 47%, respectively, concurring with results reported in the literature. The crack density at 100× magnification increased with increasing load level in all cases, with Kevlar having the lowest and Flax having the highest. Furthermore, the Kevlar/Flax hybrid displayed better performance than pure Flax, with lower crack density and improved crack initiation and propagation within the composite. Thus, the combined use of both methods to accelerate testing is recommended because it resulted in good and reliable predictions of high-cycle fatigue strength.

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)0.001
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 score0.035
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.032
GPT teacher head0.277
Teacher spread0.245 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and ApplicationsSame topicNatural Fiber Reinforced CompositesFrench-language works237,207