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Record W2004411711 · doi:10.1002/pc.23522

The effects of long‐term exposure of flax fiber reinforced polymer to salt solution at high temperature on tensile properties

2015· article· en· W2004411711 on OpenAlexaff
Kenneth Mak, Amir Fam, Colin MacDougall

Bibliographic record

VenuePolymer Composites · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceFibre-reinforced plasticUltimate tensile strengthComposite materialGlass fiberModulusComposite numberFiberYoung's modulusNatural fiberPolymer

Abstract

fetched live from OpenAlex

Most research on natural fiber composites has been primarily conducted on randomly‐oriented fibers. This study is focused on the short‐ and long‐term performances of flax fiber‐reinforced polymer (Flax‐FRP) made from continuous unidirectional fiber mats, and compares it to Glass‐FRP composite. The study looked into the effect of number of layers on properties, comparing wet layup (WL) to vacuum bag (VB) molding, and aging in a 3.5% salt solution for up to 365 days at 23, 40, and 55°C. Results show that Flax‐FRP has a tensile strength and modulus of one third the values of Glass‐FRP. Using the VB process, Flax‐FRP showed a strength and modulus 18 and 36% higher, respectively, than WL specimens. As the number of layers increased from one to five, the strength and modulus also increased but stabilized at three layers. After 365 days of conditioning at 23, 40, and 55°C, WL specimens showed a strength retention of 81, 73, and 69%, respectively. Using the Arrhenius relationship, it was estimated that both WL and VB Flax‐FRP would retain 60% of their tensile strength after 100 years of saltwater exposure at an annual mean temperature of 10°C. POLYM. COMPOS., 37:3234–3244, 2016. © 2015 Society of Plastics Engineers

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 score0.012
Threshold uncertainty score0.956

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 science0.0010.000
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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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

Citations32
Published2015
Admission routes1
Has abstractyes

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