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Record W2027318502 · doi:10.1179/wsc.2007.17.6.333

Stress-Strain Response of Wood Under Radial Compression. Part 3 - Prediction Using Cellular Theory

2007· article· en· W2027318502 on OpenAlexfundno aff
Ying Hei Chui, T Tabarsa

Bibliographic record

VenueJournal of the Institute of Wood Science · 2007
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCompression (physics)Composite materialStress (linguistics)Elastic modulusStress–strain curveStructural engineeringRadial stressModulusStrain (injury)Composite numberYield (engineering)Deformation (meteorology)Engineering

Abstract

fetched live from OpenAlex

As most wood-based composite products are made by compressing wood in the transverse direction, usually at elevated temperature, stress-strain response of wood under this stressing mode has a great influence not only on the design of the manufacturing process, but also on the end product properties. This paper describes a study to develop a mechanics-based method of predicting the complete stress-strain response of wood under radial compression, based on material properties of the cell wall and the dimensions of the cellular structure. The basis of the method is two previously developed micro-mechanical models for predicting gross elastic modulus and yield stress of wood under radial compression. Verification tests were conducted using white spruce specimens. It is demonstrated that using these two models, the entire stress-strain response encompassing the elastic, plastic and densification regions can be predicted with good accuracy.

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)0.002
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 score0.149
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.242
Teacher spread0.213 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

Explore more

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