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Record W2031932856 · doi:10.1080/13632469.2013.767759

Numerical Modeling of Slender Reinforced Concrete Shear Wall Shaking Table Tests Under High-Frequency Ground Motions

2013· article· en· W2031932856 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Earthquake Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpenSeesEarthquake shaking tableStructural engineeringShear wallFinite element methodStiffeningNonlinear systemReinforced concreteStiffnessShear (geology)EngineeringMaterials scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

This article presents the numerical modeling of large-scale shake table tests of slender 8-story reinforced concrete (RC) shear wall specimens. Nonlinear time history analyses are carried out using reinforced concrete fiber elements (OpenSees, OS) and the finite element (FE) methods (VecTor2, VT2). The effects of the modeling assumptions are investigated, including: (a) the tension stiffening effect, (b) damping, (c) smeared vs. lumped reinforcement, and (d) the use of effective shear stiffness in OS. Good agreements are obtained between the numerical and experimental results. Using the proposed numerical modeling strategy, it is possible to investigate the nonlinear dynamic responses of slender RC wall structures with confidence.

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.

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 score0.220
Threshold uncertainty score0.850

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 communication0.0000.001
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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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