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Record W4395450572 · doi:10.2749/manchester.2024.0493

A Case Study on the Structural Assessment of an Existing Through Arch Truss Bridge

2024· article· en· W4395450572 on OpenAlexaboutno aff
Dillon Betts, Aaron Ferguson, Jorge Pérez Armiño, Will Crocker

Bibliographic record

VenueReport · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)TrussStructural engineeringArchStructural health monitoringTruss bridgeEngineeringBeam bridgeFinite element methodAeroelasticityExpansion jointForensic engineeringSpan (engineering)Civil engineeringAerodynamics

Abstract

fetched live from OpenAlex

The Seal Island Bridge is a steel through-arch truss bridge in Cape Breton Island, Nova Scotia, Canada with a main span of 152 m over navigable waters. At over 60 years in service, the bridge is near the end of its design life and showing structural and operational difficulties such as a previously failed truss diagonal, the presence of tack welds throughout the structure, cracked floorbeams and wind- induced vibrations. As a part of this study, a series of detailed and focused bridge inspections, including structural health monitoring (SHM), were performed to inform the structural analysis. To assess the structure, a finite element (FE) model was created and calibrated using SHM data and the inspection findings. Additionally, a wind buffeting analysis was performed to refine the wind loading for the assessment. Based on the results of the analysis and investigations, a rehabilitation plan was developed to ensure that the bridge could remain in service for an additional 15 years.

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)0.002
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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.153
GPT teacher head0.460
Teacher spread0.307 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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