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Record W1964615048 · doi:10.1139/l06-007

Advanced modelling of concrete deterioration due to reinforcement corrosion

2006· article· en· W1964615048 on OpenAlexfundvenueno aff
O. Burkan Isgor, A. Ghani Razaqpur

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCorrosionDurabilityMaterials scienceChlorideNonlinear systemFinite element methodReinforcementMoistureMetallurgyStructural engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

A comprehensive model is presented for predicting the rate of steel corrosion in concrete structures and the consequent formation and propagation of cracks around the steel reinforcement. The corrosion model considers both the initiation and the propagation stages of corrosion. Processes commencing in the initiation stage, such as the transport of chloride ions and oxygen within the concrete and variation in temperature and moisture, are assumed to continue in the propagation stage while active corrosion is occurring contemporaneously. This allows the model to include the effects of changes in exposure conditions on the corrosion rate and the effects of the corrosion reactions on the transport properties of concrete. The corrosion rates are calculated by applying the finite-element solution of the Laplace equation for electrochemical potential, with appropriate boundary conditions. Because these boundary conditions are nonlinear, a nonlinear solution algorithm is used. The results of the analysis are compared with available test data, and the comparison is found to be satisfactory. Key words: reinforced concrete, steel corrosion, finite-element modelling, durability.

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: none
Teacher disagreement score0.556
Threshold uncertainty score0.591

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 head0.009
GPT teacher head0.178
Teacher spread0.168 · 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

Citations25
Published2006
Admission routes2
Has abstractyes

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