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Record W2897807840 · doi:10.3390/fib6040081

Effect of Density and Fiber Size on Porosity and Thermal Conductivity of Fiberboard Mats

2018· article· en· W2897807840 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFibers · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsMinistère des Ressources naturelles et des ForêtsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPorosityMaterials scienceComposite materialThermal conductivityFiberFiberboardThermal conduction

Abstract

fetched live from OpenAlex

The thermal conductivity and porosity of fiberboard mats are crucial parameters for efficient energy consumption of the hot-pressing process and for final panel quality. In this work, the effect of fiber size and mat density on porosity and thermal conductivity of the mat were investigated. The fiber size was characterized as fine, medium and coarse. The mat porosity was measured by image analysis using the black and white contrast method. The thermal conductivity was determined at different density levels with a temperature gradient of 1.6 °C mm−1 and 7.6% (s = 0.3) moisture content. The results showed that fiber size was a dominant variable governing heat conduction and mat porosity. The mats made with medium size fibers showed a higher resistance to compression. The thermal conductivity of coarse fiber mats decreased drastically between 700 kg m−3 and 810 kg m−3. This was likely due to a higher fracture frequency observed for coarse fibers in comparison to the other fiber sizes studied. Hence, the fine and medium fibers conducted heat more efficiently. Moreover, fiber bundles and fractured fibers were observed during the mat porosity measurements, principally in mats made with fine fiber size.

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.

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 score0.019
Threshold uncertainty score0.500

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 studies0.0000.001
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 head0.006
GPT teacher head0.242
Teacher spread0.236 · 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