MétaCan
Menu
Back to cohort
Record W2129462293 · doi:10.5772/50070

Dynamic Behaviour of the Confederation Bridge Under Seismic Loads

2012· book-chapter· en· W2129462293 on OpenAlexaboutno aff
Lan Lin, N. Naumoski, Murat Saatçioğlu

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)GeologySeismologyStructural engineeringComputer scienceForensic engineeringEngineeringMedicine

Abstract

fetched live from OpenAlex

The 12.9 km Confederation Bridge, crossing the Northumberland Strait in eastern Canada, is one of the longest reinforced concrete bridges in the world. In the design of the bridge, the seismic hazard for the bridge location was represented by a seismic design spectrum. This spectrum was derived by applying spectral amplification factors to the peak ground acceleration, velocity and displacement, corresponding to the design life of the bridge of 100 years. The design forces and displacements due to seismic loads were computed using the modal response spectrum method. This paper describes results from a study on the dynamic behaviour of the Confederation Bridge due to seismic loads. The seismic hazard for the bridge location was represented by a uniform hazard spectrum corresponding to the most recent seismic hazard models. For the purpose of the seismic analysis of the bridge, a finite element model was developed using 3-D beam elements. The model was calibrated using measured data of the bridge vibrations during a dynamic load test. Dynamic time-history analyses were conducted by applying seismic excitation motions corresponding to the seismic hazard of the location. The bending moments and the displacements obtained from the seismic analysis were compared with the design values. It was found that the seismic effects used in the design are quite representative of the seismic hazard of the bridge location. (A)

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score0.837

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 head0.015
GPT teacher head0.223
Teacher spread0.207 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreOther

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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInTech eBooksSame topicSeismic Performance and AnalysisFrench-language works237,207