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Record W2318090868 · doi:10.1061/40937(261)64

Virtual Experiments to Investigate Steel Corrosion in Concrete

2007· article· en· W2318090868 on OpenAlexaff
Mohammad Pour‐Ghaz, O. Burkan Isgor, Pouria Ghods

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsCorrosionBoundary element methodComputer scienceProcess (computing)Service lifeFinite element methodRelaxation (psychology)Boundary value problemLaplace transformBoundary (topology)Domain (mathematical analysis)Structural engineeringLaplace's equationMechanical engineeringMaterials scienceEngineeringMathematicsMathematical analysisComposite material

Abstract

fetched live from OpenAlex

Virtual experiments are one of the integral parts of the advanced civil engineering practice since they eliminate time-consuming and expensive laboratory studies, and they are useful for educational and training purposes. In the present work, a number of virtual experiments for investigating the corrosion of reinforcement in concrete are designed, and the effect of different parameters on the corrosion process is examined. The design of the experiments is based on non-linear solution of Laplace's equation with polarized surface boundary conditions by the finite element method, for which an under-relaxation technique is implemented. Using the results of the virtual experiments, a closed-form solution for the considered domain is obtained. By using this solution, the effect of a number of factors that affect the corrosion process can be investigated; an example of this investigation is presented. These experiments can also be effectively used for service life design and structural health and integration monitoring purposes; these two approaches are discussed in detail.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.420

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 head0.028
GPT teacher head0.312
Teacher spread0.284 · 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 designBench or experimental
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

Citations2
Published2007
Admission routes1
Has abstractyes

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