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Record W4380450999 · doi:10.52202/069179-0305

EXPERIMENTAL INVESTIGATIONS ON CLT PANELS WITH OPENINGS

2023· article· en· W4380450999 on OpenAlexafffundabout
Xiaoyue Zhang, Lu Xuan, Weitian Li, Thomas Tannert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Northern British Columbia
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaUniversity of Northern British Columbia
KeywordsStiffnessCross laminated timberStructural engineeringShear (geology)Shear wallMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

The design of cross-laminated timber (CLT) shear walls demands careful consideration.In order to reduce cost and speed up construction time, large panel sizes are often preferred, yet sometimes openings are required for architectural purposes.However, the Canadian Standard for Engineering Design in Wood (CSA O86-19) prohibits openings in CLT shear walls due to a lack of research quantifying the reduction of stiffness as a function of opening size.To address this research gap, the impact of opening size on the stiffness of CLT panels was investigated.A total of 43 tests were conducted on panels with two different aspect ratios, two different thicknesses, and various opening sizes.The results indicate that the panel stiffness decreases non-linearly with an increase in opening size.However, even opening sizes large in relation to the panel width have only a minimal impact on the panel stiffness.These findings provide valuable insights for future design provisions for openings in CLT shear walls.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.002

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 head0.039
GPT teacher head0.224
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes3
Has abstractyes

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Same topicWood Treatment and PropertiesFrench-language works237,207