MétaCan
Menu
Back to cohort
Record W1834043381 · doi:10.1139/cjce-2011-0370

Characteristics of dynamic monitoring data and observed behaviour of the Confederation Bridge due to operational load variations

2013· article· en· W1834043381 on OpenAlexaffvenue
Nicolás A. Londoño, David T. Lau, Muhammad Moshiur Rahman

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsBridge (graph theory)VibrationModalStructural health monitoringStructural engineeringOperational Modal AnalysisCalibrationField (mathematics)Ambient vibrationDynamic loadingModal analysisEngineeringEnvironmental scienceAcousticsFinite element methodMaterials science

Abstract

fetched live from OpenAlex

A dynamic monitoring system has been installed on the Confederation Bridge to capture ambient and triggered vibration responses of the bridge due to wind, traffic, ice, and earthquake loads. The field monitoring data and observed behaviour of the bridge provide useful information and insights for practical application of vibration based structural health monitoring techniques in actual field operating conditions. In the present study, monitoring data collected under different loading scenarios have been analyzed to better understand the variability characteristics of the field measured data and extracted dynamic properties of the bridge. Calibration of computer bridge models using the monitoring data is presented. The field measured vibration modal frequencies differ only by 2% to 4% from the calibrated computer models. Field observed vibration mode shapes and damping ratios of the bridge are also presented. The frequency contents of the bridge responses and their variability under different loading scenarios are presented.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.384

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 head0.028
GPT teacher head0.245
Teacher spread0.217 · 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 designObservational
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

Citations14
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Health Monitoring TechniquesFrench-language works237,207