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Record W4380449509 · doi:10.52202/069179-0324

IN-PLANE DEFLECTION OF CROSS-LAMINATED TIMBER DIAPHRAGMS

2023· article· en· W4380449509 on OpenAlexafffund
Mahboobeh Fakhrzarei, Hossein Daneshvar, Ying Hei Chui

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesFPInnovations
KeywordsStructural engineeringPerpendicularCross laminated timberStiffnessDeflection (physics)Finite element methodMaterials scienceParametric statisticsEngineeringGeometryPhysicsMathematicsOptics

Abstract

fetched live from OpenAlex

Cross-Laminated Timber (CLT) is a reliable alternative to heavy structural components due to its dimensional stability and environmental benefits.However, there is currently no universally accepted design method for calculating the load-bearing capacity and deformation of a CLT diaphragm.The main objective of this study is to develop an analytical model for diaphragm deflection calculation when the major direction of panels is perpendicular to the load and confirm the results with the Finite Element (FE) analysis.In the absence of an experimental study aligned with the derived formula, an FE model was developed based on a full-scale diaphragm test subjected to loading parallel and perpendicular to the panel length.A parametric study was performed on the influence of the diaphragm length and the panel-to-panel connection stiffness.The contribution of bending, shear, and connection's slip to the total diaphragm deflection was quantified.The study reveals that the flexibility of the floor is primarily influenced by two factors: the shear deformation of the CLT panels when the load is perpendicular to the panel length and the stiffness of the panel-topanel connection when the load is parallel to the panel length.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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 routes2
Has abstractyes

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Same topicWood Treatment and PropertiesFrench-language works237,207