MétaCan
Menu
Back to cohort
Record W4380450671 · doi:10.52202/069179-0364

AN ANALYTICAL MODEL TO INVESTIGATE THE EFFECT OF DIAPHRAGMS ON THE ELASTIC BEHAVIOUR OF MULTI-STOREY COUPLED-PANEL CLT SHEARWALLS

2023· article· en· W4380450671 on OpenAlexaff
Damian Oliveira, Ali Mikael, Daniele Casagrande, Ghasan Doudak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsCanadian Wood Council
Fundersnot available
KeywordsStructural engineeringFinite element methodDiaphragm (acoustics)EngineeringVibrationComputer scienceAcousticsPhysics

Abstract

fetched live from OpenAlex

This study develops an analytical model to describe the behaviour of multi-storey multi-panel CLT shearwalls, specifically accounting for cumulative loads between storeys and the effect of the diaphragm.The analysis considers the contribution of hold-downs, wall-to-floor connections, and panel-to-panel joints, as well as loads transferred from storeys above.The analysis has been developed for shearwalls acting as a series of coupled panels (CP) each individually rotating about a corner.Force transfer between storeys is implemented by distributing reactions through the upper floor diaphragm and a direct force from the upper storey's hold-down.Structuring the equations this way allows for a simplified formulation while including several components of the system's complex behaviour.Two-dimensional finite element modelling is used to verify the accuracy of the developed model.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.280
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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicStructural Load-Bearing AnalysisFrench-language works237,207