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Record W2111319547 · doi:10.1002/pen.20632

Measurement and prediction of thermal conductivity for hemp fiber reinforced composites

2007· article· en· W2111319547 on OpenAlexaff
Tayebeh Behzad, Mohini Sain

Bibliographic record

VenuePolymer Engineering and Science · 2007
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceComposite materialThermal conductivityHeat fluxThermalFiberThermal conductivity measurementTransverse planeDrop (telecommunication)Heat transferStructural engineeringThermodynamicsMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The thermal conductivity of hemp fiber reinforced polymer composites were studied from the steady state temperature drop across samples exposed to a known heat flux. The transverse and in‐plane thermal conductivities for oriented and randomly oriented composites for different volume fractions of fiber were investigated. Experimental results showed that the orientation of fibers has a significant effect on the thermal conductivity of composites. To validate the experimental results, the heating tests for the thermal conductivity measurements were simulated by a finite element model using the thermal conductivity values obtained from the experiments. Predicted temperatures show close agreement with measured temperatures. Moreover, the experimental results of thermal conductivities of composites at different directions were compared with two theoretical models and illustrated good agreement between the obtained results and models. POLYM. ENG. SCI. 47:977–983, 2007. © 2007 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.226
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 source (direct Gemma or distilled Codex), 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

Citations118
Published2007
Admission routes1
Has abstractyes

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