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Record W4311844188 · doi:10.1139/cjce-2022-0257

Development of ductility-related modification factor for CLT-coupled wall buildings with replaceable shear link coupling beams

2022· article· en· W4311844188 on OpenAlexaffvenueabout
Biniam Tekle Teweldebrhan, Marjan Popovski, Jasmine B. W. McFadden, Solomon Tesfamariam

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsNational Research Council CanadaCanadian Cardiovascular SocietyFPInnovationsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsStructural engineeringShear wallDuctility (Earth science)Building codeInduced seismicityCoupling (piping)Seismic analysisGround motionFactor of safetyEngineeringCivil engineeringGeotechnical engineeringMaterials scienceMechanical engineering

Abstract

fetched live from OpenAlex

The desire of using sustainable materials has reignited the interest in timber-based construction. Researchers and practitioners are developing novel timber-based structural solutions. Cross-laminated timber (CLT)-coupled wall is a recently proposed system for potential use in mid- and high-rise timber construction. The National Building Code of Canada, however, does not include this system and, consequently, the seismic force modification factors are not available. This study evaluated the ductility-related force modification factor ( R d ) using the FEMA P-695 procedure. Nine archetype buildings were designed considering different design parameters: building storey height, CLT wall configuration, and coupling ratios. Using 30 ground motion records (bi-directional), rigorously selected for seismicity of Vancouver, BC, Canada, incremental dynamic analyses were performed. Collapse margin ratios were calculated to assess the adequacy of the trial R d factors. Using an over-strength factor of 1.5, R d = 4 is found to be acceptable for this system.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.625

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 head0.011
GPT teacher head0.189
Teacher spread0.178 · 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 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

Citations11
Published2022
Admission routes3
Has abstractyes

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