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Record W2095885040 · doi:10.1002/eqe.455

A reassessment of dynamic characteristics of the Quincy Bayview Bridge using output‐only identification techniques

2005· article· en· W2095885040 on OpenAlexafffund
Brad Pridham, John C. Wilson

Bibliographic record

VenueEarthquake Engineering & Structural Dynamics · 2005
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBridge (graph theory)Identification (biology)EngineeringStructural engineeringComputer scienceBiologyEcology

Abstract

fetched live from OpenAlex

Abstract A reassessment of the dynamic characteristics of the 542 m cable‐stayed Bayview Bridge in Quincy, Illinois, is presented using a newly developed output‐only system identification technique. The technique is applied to an extensive set of ambient vibration response data acquired from the bridge in 1987. Vertical, torsional and transverse modal frequencies of the deck are identified, and uncertainty in damping values are estimated using an automated procedure on several redundant measurements at four locations. Important practical implementation issues associated with the implementation of the procedure and selection of algorithm design parameters for stochastic subspace identification techniques are discussed. An overall mean and standard deviation of damping of 1.0±0.8% is estimated considering all identified vertical, torsional and transverse modes in the 0–2 Hz band. The mean damping for the fundamental vertical mode (0.37 Hz) is identified as 1.4±0.5%, and for the first coupled torsion–transverse mode (0.56 Hz) is identified as 1.1±0.8%. Variability in the damping estimates is shown to decrease as estimated modal RMS acceleration levels increase. Standard deviations on estimated damping range from 0.05% to 2%. The results are shown to be a substantial improvement in the evaluation of damping compared to earlier spectral analysis conducted on the same data set. Copyright © 2005 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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

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 communication0.0010.000
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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations15
Published2005
Admission routes2
Has abstractyes

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