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Record W2171953564 · doi:10.1177/0731684414523691

The effect of temperature on creep behavior of wood-plastic composites

2014· article· en· W2171953564 on OpenAlexaff
Feng‐Cheng Chang, Frank Lam, John F. Kadla

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCreepMaterials scienceComposite materialWood flourStress (linguistics)StiffnessPower law

Abstract

fetched live from OpenAlex

The creep properties of wood-plastic composites limit their application, particularly in temperature variations affecting long-term performance. In this study, the effect of temperature was studied based on dynamic mechanical analysis spectra and isochrones and a newly developed stress-temperature incorporated creep equation. According to the dynamic mechanical analysis spectra, the addition of a higher content of wood flour resulted in higher moduli, indicating increased stiffness and lower mechanical loss factor. According to the isochrones, the creep strain of wood-plastic composites increased with elevated temperatures and stresses at the same time point. Moreover, the strain increased almost linearly with increasing stress at lower temperatures but became nonlinear with elevated temperature. With these findings, a stress-temperature incorporated creep equation was developed based on short-term creep tests. This empirical equation incorporates the effect of temperature in a power law equation. Good agreement was observed between the equation and experimental results.

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)0.001
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 score0.008
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.004
GPT teacher head0.217
Teacher spread0.213 · 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
Published2014
Admission routes1
Has abstractyes

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