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Record W1943833013 · doi:10.1139/l2012-032

Effects of column and superstructure stiffness on the seismic response of bridges in the transverse direction

2013· article· en· W1943833013 on OpenAlexafffundvenueabout
Payam Tehrani, Denis Mitchell

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSubstructureStructural engineeringSuperstructureStiffnessDuctility (Earth science)Transverse planeSeismic analysisColumn (typography)AbutmentEngineeringMaterials scienceGeotechnical engineeringConnection (principal bundle)Composite material

Abstract

fetched live from OpenAlex

The transverse seismic responses of continuous 4-span bridges designed based on the 2006 Canadian Highway Bridge Design Code were studied using inelastic time history analyses. A total of 648 bridge configurations were considered in which the column heights, column diameters, superstructure stiffness and mass as well as abutment restraint conditions were studied. The maximum ductility demands obtained using elastic and inelastic analyses were compared to study the influence of the degree of irregularity. The effects of column stiffness ratios and superstructure to substructure stiffness ratios on the maximum ductility demands and concentration of ductility demands were investigated. A number of different regularity indices were compared to determine the suitability of these different indices in predicting the influence of irregularity. This study demonstrates the conservative nature of the 2006 Canadian Highway Bridge Design Code and provides some guidance on factors for determining the degree of irregularity and suitable regularity indices when carrying out nonlinear dynamic analyses of bridges.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.230

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 head0.003
GPT teacher head0.153
Teacher spread0.150 · 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

Citations22
Published2013
Admission routes4
Has abstractyes

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