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Record W2921213258 · doi:10.2749/vancouver.2017.1981

Vibration Testing of Scaled Cable-Stayed Bridges

2017· article· en· W2921213258 on OpenAlexaff
Diego Padilha, Yumi Araki, Kaveh Arjomandi, Jared McGinn

Bibliographic record

VenueReport · 2017
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsGovernment of New BrunswickTransport CanadaUniversity of New Brunswick
Fundersnot available
KeywordsModalVibrationAccelerometerBridge (graph theory)SimilitudeStructural engineeringDynamic testingOperational Modal AnalysisModal analysisScale modelModal testingEngineeringScale (ratio)Finite element methodComputer scienceAcousticsAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

<p>In this article, the development of a 1/75 dynamic small-scale model of the Hawkshaw Bridge and its modal identification are presented. The results are also compared with the vibration tests performed on the prototype structure. The Hawkshaw Bridge is a cable-stayed bridge in New Brunswick. The scaled model is 4.4 metres long compared to the actual length of 332 metres. The scale model was designed to stay within the elastic limits under the performed tests. Similitude laws were strictly followed to develop a structural model that complies with the dynamic similitude requirements. Random vibration sources were introduced to the scaled structure to simulate operational dynamic loads that the prototype structure experience. The response of the model was recorded using five tri- axial accelerometers. Using operational modal analysis, modal properties of the scaled model are estimated. The results were used to correlate the field vibration test data to the laboratory experiments.</p>

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 score0.222
Threshold uncertainty score0.266

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 head0.048
GPT teacher head0.321
Teacher spread0.273 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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