MétaCan
Menu
Back to cohort
Record W2082170679 · doi:10.1080/10286600212160

Effect of Reinforcement Corrosion on Reliability of Bridge Girders

2002· article· en· W2082170679 on OpenAlexafffund
Jie Sun, Han Hong

Bibliographic record

VenueCivil Engineering and Environmental Systems · 2002
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCorrosionGirderReliability (semiconductor)Service lifeStructural engineeringBridge (graph theory)Nonlinear systemMaterials scienceReinforcementEngineeringComposite material

Abstract

fetched live from OpenAlex

Aging reinforced concrete structures have been not only subjected to in-service loading but also exposed to an aggressive environment which will cause corrosion of reinforcing steels embedded in concrete. An approach that is akin to the nested reliability method is proposed for the time-dependent reliability analysis of bridge girders under corrosion attack. The approach can be used to investigate directly the effects of the uncertainty in surface chloride concentration and critical chloride concentration for corrosion initiation, and the possible nonlinear corrosion growth on the reliability. The consideration of the nonlinear corrosion growth is due to the fact that the corrosion current density may not be a constant. Analyses of the reliability of bridge girders to the parameters governing the corrosion are performed using the proposed approach and typical statistics of load effects and material strength parameters. Results suggest that consideration of the nonlinear corrosion growth is very important in determining the remaining service life of existing concrete structures, and that the uncertainty in the variables controlling the corrosion initiation has only small effect on the estimated time-dependent reliability.

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)0.007
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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 head0.005
GPT teacher head0.163
Teacher spread0.158 · 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

Citations10
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueCivil Engineering and Environmental SystemsSame topicConcrete Corrosion and DurabilityFrench-language works237,207