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Record W2952570268 · doi:10.32604/sdhm.2019.04743

Bending and Rolling Shear Properties of Cross-Laminated Timber Fabricated with Canadian Hemlock

2019· article· en· W2952570268 on OpenAlexaboutno aff
Gengmu Ruan, Haibei Xiong, Jiawei Chen

Bibliographic record

VenueStructural durability & health monitoring · 2019
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceStructural engineeringDeflection (physics)Failure mode and effects analysisShear modulusShear (geology)Composite materialDirect shear testBendingFlexural strengthCross laminated timberEngineering

Abstract

fetched live from OpenAlex

In this paper, bending performance and rolling shear properties of cross-laminated timber (CLT) panels made from Canadian hemlock were investigated by varied approaches. Firstly, three groups of bending tests of three-layer CLT panels with different spans were carried out. Different failure modes were obtained: bending failure, rolling shear failure, bonding line failure, local failure of the outer layer and mixed failure mode. Deflection and strain measurements were employed to calculate the global and local modulus of elastic (MOE), compared with the theoretical value. In addition, a modified compression shear testing method was introduced to evaluate the rolling shear strength and modulus, compared with the results from strain measurements in bending shear tests. According to testing results, bonding line failure and rolling shear failure were dominant failure modes in bending tests, and the theoretical value of bending property was beyond the average level of the calculating results obtained from both deflection and strain measurements. In addition, the rolling shear strength and modulus obtained from compression shear tests were relatively smaller than those from bending tests.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.977

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 head0.016
GPT teacher head0.242
Teacher spread0.225 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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