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Record W1827672843 · doi:10.1139/cjce-2011-0263

A methodology for evaluating the effects of spalling on the structural capacity of reinforced concrete bridge girders

2014· article· en· W1827672843 on OpenAlexafffundvenue
Jeffrey Luckai, Maria Anna Polak, Scott Walbridge

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Waterloo
FundersMinistère des Transports
KeywordsSpallStructural engineeringBridge (graph theory)GirderBeam bridgeEngineeringPrioritizationCorrosionComputer scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Corrosion of the reinforcing steel is a primary deterioration mechanism for reinforced concrete bridges. The spatial distribution of such spalling, relative to bar splices and laps, has not been considered in previous studies and may have a significant influence on structural capacity. In this paper, a modified area concept for considering this spalling is proposed. A methodology has been developed that employs this concept for the practical evaluation of existing bridges. It uses graphical spalling surveys, reinforcement layout information, and existing information regarding material and geometric properties as inputs for the flexural and shear analysis of deteriorated bridge girders. This methodology is easily adapted for full bridge analysis and to consider the effects of bar section loss and bond deterioration. A case study bridge is evaluated to show that this methodology offers a viable tool for the rapid assessment of spalled bridge girders to facilitate the prioritization of rehabilitation projects.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.258
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
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 head0.050
GPT teacher head0.261
Teacher spread0.211 · 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

Citations7
Published2014
Admission routes3
Has abstractyes

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