MétaCan
Menu
Back to cohort
Record W4246702002 · doi:10.2495/eres1300131

Influence of diaphragm flexibility on lateral load distribution between shear walls in light wood frame buildings

2013· article· en· W4246702002 on OpenAlexafffund
Zhiyong Chen, Ying Hei Chui, C. Ni, Ghasan Doudak, M. Mohammad

Bibliographic record

VenueWIT transactions on the built environment · 2013
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsUniversity of OttawaFPInnovationsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShear wallStructural engineeringDiaphragm (acoustics)StiffnessShear (geology)Flexibility (engineering)Spring (device)Structural loadMaterials scienceGeologyEngineeringVibrationComposite materialAcousticsPhysicsMathematics

Abstract

fetched live from OpenAlex

In light wood frame buildings, diaphragm flexibility influences the load distribution between shear walls under lateral load induced by earthquake or wind action, which is important for structural design.A multiple spring model with the ability to represent the load-transferring behaviour of this complex lateral load resisting system of light wood frame buildings was developed.The developed model was validated with results from the more sophisticated model, spring deep-beam model.The lateral load distribution between shear walls with various stiffness ratios of diaphragm to shear wall was also investigated.Based on preliminary findings from this study, contrary to common belief, the forces transferred by a semi-rigid diaphragm to the supporting shear walls, may be higher than those predicted by flexible and rigid diaphragm assumptions.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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 designSimulation or modeling
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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueWIT transactions on the built environmentSame topicTree Root and Stability StudiesFrench-language works237,207