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Record W2251771966

Theoretical Modeling of Bonding Characteristics and Performance of Wood Composites. Part III. Bonding Strength Between Two Wood Elements

2007· article· en· W2251771966 on OpenAlexfundno aff
Guangbo He, Changming Yu, Chunping Dai

Bibliographic record

VenueWood and Fiber Science (Society of Wood Science and Technology) · 2007
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersNatural Resources CanadaCanadian Forest ServiceNatural Sciences and Engineering Research Council of CanadaU.S. Forest ServiceFPInnovations
KeywordsComposite materialMaterials scienceBond strengthCompactionUltimate tensile strengthSolid woodBonding strengthAdhesive
DOInot available

Abstract

fetched live from OpenAlex

The bonding characteristics between two wood elements (strands) were investigated using experimental and modeling approaches.Based on the mechanism of surface contact and resin coverage, the model predicted the apparent bond strength as a function of compaction ratio, resin content, and transverse tensile strength of wood.Experimental tests were conducted to determine the resin coverage and apparent bond strength of two overlapped aspen (Populus tremuloides) strands under uniform and random resin distributions.The model was validated by close agreement between the predictions and the experimental results.The results showed that the optimum compaction ratio should be between 1.25 and 1.30 for the maximum contact and apparent bond strength.Further densification would induce damage to wood and inhibit final bonding performance.The apparent bond strength was proved to be related to resin content through the direct impact of resin area coverage.The results also suggested that one could save resin consumption by reducing spot thickness and increasing spot number or coverage.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.274
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.004
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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.

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

Citations14
Published2007
Admission routes1
Has abstractyes

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