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Record W3153927520 · doi:10.1139/cjce-2020-0036

Seismic reliability assessment of base-isolated bridges in Quebec

2021· article· en· W3153927520 on OpenAlexaffvenueabout
Maaly Nassar, Lotfi Guizani, Marie‐José Nollet, Antoine Tahan

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsStructural engineeringPierLimit state designSeismic hazardReliability (semiconductor)Bridge (graph theory)EngineeringSeismic riskDisplacement (psychology)Seismic loadingMonte Carlo methodIncremental Dynamic AnalysisSeismic analysisGeotechnical engineeringMathematicsStatisticsCivil engineeringPhysics

Abstract

fetched live from OpenAlex

The aim of this work is to estimate the seismic reliability of a simple typical two-span lifeline base-isolated bridge designed to behave essentially elastic or as per the Canadian Highway Bridge Design Code, for seven localities in Quebec. Two limit states are considered for possible failure due to unacceptable damage: flexure at the pier-base and displacement within the seismic isolation systems (SIS). The main problem random variables considered and modeled are seismic hazard, temperature, pier base dimensions, and material mechanical properties. The Monte Carlo method was used to evaluate the probability of failure and the reliability of each limit state. Preliminary results reveal that notwithstanding the large temperature and seismic hazard variabilities between the seven sites in Quebec, the global bridge reliability indices are almost uniform, approximately 3.45 ± 0.02. Furthermore, the security factor (i.e., 1.25) on the SIS displacement capacity results in reliability indices for SIS displacement that are not levelled with the flexural reliability indices and requires further examination and consideration.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.996

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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 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

Citations5
Published2021
Admission routes3
Has abstractyes

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