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Record W3216381432 · doi:10.1177/87552930211053347

Inelastic seismic shear amplification due to higher mode effects in reinforced concrete coupled walls

2021· article· en· W3216381432 on OpenAlexafffundabout
Gabriel Rivard, Steeve Ambroise, Patrick Paultre

Bibliographic record

VenueEarthquake Spectra · 2021
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsQ & T ResearchUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShear wallStructural engineeringParametric statisticsCantileverShear (geology)Seismic analysisReinforced concreteGeologyGeotechnical engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

Recent numerical and experimental studies on reinforced concrete shear walls and coupled walls have shown shear forces greater than expected when the walls are subjected to earthquakes at an intensity level that does not exceed the design values. This amplification of shear forces is attributable to the effects of higher modes after the walls develop a plastic hinge at the base. These effects have been recently recognized in North American design codes for cantilever walls and is currently neglected in the design of ductile coupled walls. As part of the research program described in this article, a parametric study was carried out on coupled wall systems to identify the geometric and physical parameters having the greatest influence on the seismic shear amplification. Using the results of this parametric study, an extensive numerical study was conducted on classes of ductile coupled walls subjected to seismic excitation representative of Western and Eastern Canada. This extensive study led to the establishment of shear amplification prediction equations for use in building codes.

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 score0.077
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Citations10
Published2021
Admission routes3
Has abstractyes

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