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Record W2778146590 · doi:10.1680/jmacr.17.00080

A study on the effect of curing temperature and duration on rebar corrosion

2018· article· en· W2778146590 on OpenAlexaff
Hossam S. Al-alaily, Assem A. A. Hassan

Bibliographic record

VenueMagazine of Concrete Research · 2018
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCorrosionCuring (chemistry)ChlorideRebarMaterials scienceComposite materialMetallurgy

Abstract

fetched live from OpenAlex

The aim of this investigation was to study the corrosion activity in reinforced concrete exposed to different curing temperatures and durations using a wet–dry cycle corrosion test. Reinforced concrete samples were also tested under an impressed current accelerated corrosion test for comparison. In total, ten curing techniques were conducted by varying curing temperature (hot, normal and cold) and curing duration (1, 3, 7 and 28 d). These curing techniques were evaluated based on the results of wet–dry cycle, accelerated corrosion, rapid chloride permeability and chloride diffusion tests. The chloride threshold, pH value, current measurement, half-cell, mass loss and crack width readings were assessed during wet–dry cycle and impressed current corrosion tests. Heat-cured samples showed the highest chloride diffusion/permeability, shortest corrosion periods, and had the lowest chloride threshold and pH values. This was followed by cold-cured samples (28 d at 3–5°C) and then air-cured samples (28 d at 23°C). Curing samples in water for 28 d at 23°C proved to be the best curing technique. Results also showed that the impressed current accelerated corrosion test can be used effectively to evaluate and compare corrosion activities in different qualities of concrete, but cannot be used after initiation of the first crack.

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)0.001
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 score0.040
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.033
GPT teacher head0.324
Teacher spread0.291 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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