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Record W2319432215 · doi:10.1061/41016(314)121

Wind Engineering for the Confederation Bridge

2008· article· en· W2319432215 on OpenAlexaff
Jenny King, B Bakht, F. Michael Bartlett

Bibliographic record

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsAeroelasticityWind tunnelBridge (graph theory)Wind engineeringEngineeringWind speedExtrapolationDeckStructural engineeringStormReturn periodAerodynamicsMarine engineeringEnvironmental scienceMeteorologyAerospace engineering

Abstract

fetched live from OpenAlex

The Confederation Bridge was the subject of extensive wind tunnel studies to define the response characteristics and the wind loads for design. The wind climate at the site was studied to better define the wind speeds for design of the completed structure as well as loads during construction. Both section model and full aeroelastic model techniques were employed. In addition, the questions of snow accumulation on the deck and the overturning of vehicles were examined. The principal results of these studies are presented. Validation of wind tunnel model tests of long span bridges is an important component of the wind engineering of these structures. Full-scale monitoring permits a corroboration of the predicted wind-induced responses and loads and also a confirmation of the dynamic properties of the structure. Few bridges have been monitored over an extended period of time, permitting the collection of significant wind "events" in comparison with design return periods; therefore extrapolation well beyond the annual extreme is necessary. The Confederation Bridge has an extensive array of instrumentation which has been in service since the construction of the bridge in 1997. The aims of the monitoring program at the outset were focused on the ice and traffic loads on the bridge as well as an assessment of the structural properties post-construction. However, an opportunity to assess the performance of the bridge under extreme winds and hence compare to the design loads was presented during several winter storms of exceptional severity. The paper focuses on the performance of this bridge to strong wind and compares the observed behaviour to the wind tunnel tests of a full aeroelastic model in addition to the development of wind loads used for the design.

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 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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.017
GPT teacher head0.223
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2008
Admission routes1
Has abstractyes

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