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Record W1979348171 · doi:10.1515/hf.2010.080

Three-dimensional modeling of the structure formation and consolidation of wood composites

2010· article· en· W1979348171 on OpenAlexafffund
François Drolet, Chunping Dai

Bibliographic record

VenueHolzforschung · 2010
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsFPInnovations
FundersFPInnovations
KeywordsPorosityMaterials scienceComposite materialConsolidation (business)

Abstract

fetched live from OpenAlex

Abstract A new three-dimensional (3D) computer simulation model is proposed to study structure development in wood composites, particularly strand or short fiber wood composites. The model takes into account the stochastic positioning and orientation of the strands within the mat. It also predicts the response of individual strands within the structure to the compressive and shear forces produced during mat consolidation. The model provides a complete description of mat structure in three dimensions, including spatial distribution of porosity, inter-strand contact, and density. Predictions for porosity obtained with the 3D model compare very well with those from an earlier two-dimensional analytical model. Mat structure is dictated by mat density in a two-step process: rapid removal of macrovoids before the mat density reaches the original wood density and asymptotic elimination of microvoids at higher mat densification. Other factors of importance include original wood density and strand dimensions, particularly strand thickness and width. Although known for its influence on mechanical properties, strand orientation seems to have little effect on mat porosity and strand contact.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.144

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 head0.009
GPT teacher head0.183
Teacher spread0.174 · 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

Citations4
Published2010
Admission routes2
Has abstractyes

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