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

Wind Engineering for the Confederation Bridge

2008· article· en· W2319432215 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.578
Threshold uncertainty score0.582

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 head0.017
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