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Record W2511376767 · doi:10.1115/1.4034527

Assessment of Flexure Failure Models Using Loads Measured on the Conical Piers of the Confederation Bridge During 1998–2008

2016· article· en· W2511376767 on OpenAlexaffabout
Chee K. Wong, Thomas G. Brown, J. Susan Robertson

Bibliographic record

VenueJournal of Offshore Mechanics and Arctic Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPierBridge (graph theory)RubbleConical surfacePileGeologyStructural engineeringGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

The Confederation Bridge spans across the Northumberland Strait in Eastern Canada connecting Prince Edward Island to mainland Canada through New Brunswick. Due to the presence of ice during each winter, the bridge piers are subjected to ice loads. A comprehensive permanent monitoring program has been implemented to observe and measure the ice–structure interaction events at two piers since the start of the bridge operations in 1998. This study uses the derived ice loads on one pier, and the associated event attributes for 100 selected events. Flexural failure models are used to determine theoretical loads of the selected interaction events. It is found that the weight of the total ice rubble pile and the physical and mechanical properties of the ice sheet are the dominant parameters affecting the ice load exerted on the conical structure. A semi-empirical correlation is developed to relate the ice load with those parameters for the Confederation Bridge.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.260
Teacher spread0.230 · 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 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

Citations2
Published2016
Admission routes2
Has abstractyes

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