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Record W2999722200 · doi:10.1002/app.48992

About the influence of temperature and environmental relative humidity on the longitudinal and transverse mechanical properties of elementary alfa fibers

2020· article· en· W2999722200 on OpenAlexaff
Mokhtar Khaldi, Mohamed Mokhtar Bouziane, Alexandre Vivet, Habiba Bougherara

Bibliographic record

VenueJournal of Applied Polymer Science · 2020
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceComposite materialRelative humidityTransverse planeUltimate tensile strengthModulusNanoindentationHumidityThermalYoung's modulusElastic modulusStructural engineering

Abstract

fetched live from OpenAlex

Abstract Composites reinforced with plant‐based fibers present a high potential for valorization in new industrial applications due to their good specific mechanical characteristics, renewability, and recyclability. In order to accelerate their wide industry adoption, it is critical to assess their behavior and durability in heat and humid environments. This article aims at investigating the effects of temperature and relative humidity (RH) on the longitudinal and transverse mechanical properties of the lignocellulosic fibers extracted from alfa plant ( Stipa tenacissima L). For this purpose, tensile and nanoindentation tests were performed on elementary alfa fibers subjected to a thermal cycle of 200°C. The fibers were held at various periods of 15, 30, 60 and 120 min. The test results showed that the longitudinal and transverse Young's moduli are moderately affected by short thermal cycles having duration of 15–30 min. However, for longer thermal cycle (i.e., 2 hr), a degradation of 21% for the transverse modulus was recorded. This degradation doubled for the longitudinal modulus (43 vs. 21%). A similar trend was observed for the breaking strength. This study also showed that the RH strongly affects the mechanical performances of alfa fibers.

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 score0.003
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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
Published2020
Admission routes1
Has abstractyes

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