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Effects of strands geometry on the physical and mechanical properties of oriented strand boards (OSBs) made from black spruce and trembling aspen

2022· article· en· W4292794195 on OpenAlexafffundabout
Biaorong Zhuang, Alain Cloutier, Ahmed Koubaa

Bibliographic record

VenueBioResources · 2022
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOriented strand boardBlack spruceSoftwoodComposite materialMaterials scienceBendingYoung's modulusFlexural strengthStructural engineeringEngineeringForestry

Abstract

fetched live from OpenAlex

Black spruce is widely used for lumber production in Eastern Canada, and it has the potential to replace trembling aspen and paper birch for oriented strand board (OSB) manufacturing. This study evaluated the bending modulus of elasticity (MOE) and modulus of rupture (MOR), the internal bond (IB), and the thickness swelling (TS) of OSB panels made from black spruce and trembling aspen strands and how they were affected by strand geometry. All the panels met the CSA O437 (1993) standard for class O-2 properties except for the TS. The strand thickness had a significantly negative effect on the bending properties but a significantly positive effect on the IB and TS properties. The strand length had a significantly positive effect on the parallel bending properties but a significantly negative effect on the perpendicular bending properties and the IB, except for the TS. The OSB panels made from aspen obtained better bending properties, while the IB and TS properties were lower than those of the OSB black spruce panels. The results indicate that black spruce strands obtained from the Eastern Canadian softwood lumber industry are suitable for OSB production, but more work is required to reduce the TS.

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 score0.010
Threshold uncertainty score0.338

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 studies0.0000.000
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 head0.011
GPT teacher head0.182
Teacher spread0.170 · 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

Citations10
Published2022
Admission routes3
Has abstractyes

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