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Record W2140821613 · doi:10.1139/cjce-2012-0243

Performance of reinforced concrete buildings during the 27 February 2010 Maule (Chile) earthquake

2013· article· en· W2140821613 on OpenAlexafffundvenueabout
Murat Saatçioğlu, Dan Palermo, A. Ghobarah, Denis Mitchell, Rob Simpson, Perry Adebar, Robert Tremblay, Carlos E. Ventura, Hanping Hong

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsWestern UniversityPolytechnique MontréalUniversity of British ColumbiaMcGill UniversityMcMaster UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShear wallReinforced concreteSeismic analysisStructural engineeringSeismic retrofitEngineeringStructural systemBuilding codeGeologyGeotechnical engineeringCivil engineering

Abstract

fetched live from OpenAlex

The paper presents observed damage in reinforced concrete buildings during the 27 February 2010 Maule earthquake in Chile. Performance of concrete frame and shear wall buildings are discussed with emphasis on seismic deficiencies in design and construction practices. It is shown that the majority of structural damage in multistorey and high-rise buildings can be attributed to poor performance of slender shear walls, without confined boundary elements, suffering from crushing of concrete and buckling of vertical wall reinforcement. Use of irregular buildings, lack of seismic detailing, and the interference of nonstructural elements were commonly observed seismic deficiencies. A comparison is made between Chilean and Canadian design practices with references made to the applicable code clauses. Lessons are drawn from the observed structural performance.

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 score0.085
Threshold uncertainty score0.617

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 head0.004
GPT teacher head0.150
Teacher spread0.147 · 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

Citations34
Published2013
Admission routes4
Has abstractyes

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