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Record W1997333048 · doi:10.1177/0021998310380286

Effect of transport properties of fiber types on steel reinforcement corrosion

2010· article· en· W1997333048 on OpenAlexaff
B. Kim, Andrew J. Boyd, J.-Y. Lee

Bibliographic record

VenueJournal of Composite Materials · 2010
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsCorrosionMaterials scienceComposite materialFiberReinforcementPolypropyleneResistPolyvinyl alcoholFiber-reinforced concrete

Abstract

fetched live from OpenAlex

This study investigated the transport properties of fiber types in concrete to evaluate their effect on the corrosion of steel reinforcement. The fibers used in this research are polypropylene (PP), polyvinyl alcohol (PVA), and hooked-end steel fiber (Steel). The addition of PVA fibers having relatively good resistance to transport properties indicated the best resistance to the initiation time of corrosion. On the other hand, the addition of PP fibers showed a relatively good resistance to corrosion, even though the specimen had a fast rate of absorption. The addition of hooked-end steel fibers that have the best ability to resist mass transport showed the earliest failure time. The localized corrosion effect of steel fibers from the repeated wet/dry cycles seems to have a considerable effect on the acceleration of corrosion nearby steel reinforcement. In addition, fiber types do not significantly resist further acceleration following the initiation of corrosion. It is worth noting that transport properties alone are not necessarily a good indicator of the effect of fibers on resistance to corrosion.

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)0.001
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 score0.005
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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