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Record W7074627553

Seismic performance evaluation of French Creek Bridge based on Canadian Highway Bridge Design Code 2015

2016· other· en· W7074627553 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2016
Typeother
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Christian ministryModalHingeSeismic analysisStructural loadAmbient vibrationSeismic loadingTransportation infrastructure
DOInot available

Abstract

fetched live from OpenAlex

Built in 1993, the French Creek Bridge is located on highway 19 on Vancouver Island, BC, Canada. The bridge is part of the British Columbia Smart Infrastructure Monitoring System (BCSIMS), funded by the Ministry of Transportation and Infrastructure (MoTI) BC, Canada. The BCSIMS is a real-time seismic monitoring program that continuously assesses the seismic conditions of the selected bridges in BC. As part of this seismic monitoring program, the seismic performance and nonlinear dynamic behavior of the FCB was evaluated by developing the 3D Finite Element (FE) model of the bridge in SAP2000. The model was updated based on the modal properties extracted from an Ambient Vibration (AV) test. The nonlinear behavior of the bridge was modeled by adding plastic hinges on the ductile components. Then the FE model was used to perform the seismic performance evaluation in accordance with the latest Canadian Highway Bridge Design Code 2015. The evaluation result shows that during major earthquake, no primary members of the bridge were damaged, the bridge will maintains repairable and operational, and should be capable of supporting the dead load and live load after earthquake.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.829

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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
Published2016
Admission routes1
Has abstractyes

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Same venuecIRcle (University of British Columbia)Same topicTheoretical and Computational PhysicsFrench-language works237,207