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Record W2160446419 · doi:10.1002/eqe.853

Collapse of a nonductile concrete frame: Shaking table tests

2008· article· en· W2160446419 on OpenAlexaff
Chiun‐Lin Wu, Wu‐Wei Kuo, Yuan‐Sen Yang, Shyh‐Jiann Hwang, Kenneth J. Elwood, Chin‐Hsiung Loh, Jack P. Moehle

Bibliographic record

VenueEarthquake Engineering & Structural Dynamics · 2008
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEarthquake shaking tableStructural engineeringReinforced concreteEarthquake engineeringGeotechnical engineeringProgressive collapseEngineeringFlexural strengthColumn (typography)Frame (networking)Shear wallShear (geology)Ground motionGeologyForensic engineering

Abstract

fetched live from OpenAlex

Abstract Post‐earthquake reconnaissance has reported the vulnerability of older reinforced concrete (RC) columns lacking details for ductile response. Research was undertaken to investigate the full‐range structural hysteretic behavior of older RC columns. A two‐dimensional specimen frame, composed of nonductile and ductile columns to allow for load redistribution, was subjected to a unidirectional base motion on a shaking table until global collapse was observed. The test demonstrates two types of column failure, including flexure‐shear and pure flexural failure. Test data are compared with various simplified assessment models commonly used by practicing engineers and researchers to identify older buildings that are at high risk of structural collapse during severe earthquake events. Comparison suggests that ASCE/SEI 41‐06 produces very conservative estimates on load–deformation relations of flexure‐shear columns, while the recently proposed ASCE/SEI 41‐06 update imposes significant modifications on the predictive curve, so that improved accuracy has been achieved. Copyright © 2008 John Wiley & Sons, Ltd.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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 designBench or experimental
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

Citations40
Published2008
Admission routes1
Has abstractyes

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