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Record W6981381879

Effect of Different Constituent Fiber, Resin, and Sizing
\nCombinations on Alkaline Resistance of Basalt, Carbon,
\nand Glass FRP Bars

2020· other· en· W6981381879 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Southern Queensland ePrints (University of Southern Queensland) · 2020
Typeother
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsFibre-reinforced plasticDurabilityGlass fiberEpoxyCorrosionFiber
DOInot available

Abstract

fetched live from OpenAlex

When used as an internal reinforcement, fiber-reinforced-polymer (FRP) composite bars are exposed to a highly alkaline (pH > 12.5) concrete environment. This study evaluated the durability of 24 types of FRP bars in a simulated alkaline concrete environment, specifically with respect to reinforcing-fiber type (carbon, basalt, and glass), fiber sizing, resin chemistry, and manufacturer. A total of 10 types of glass fibers, including two types of E-glass fibers and eight types of electrical corrosion resistance (ECR)-glass fibers, four types of basalt fibers, two types of carbon fibers, six types of resin systems based on vinyl ester, polyurethane, and epoxy resins, and five types of proprietary fiber sizings were used in manufacturing the bars. The study focused on assessing the tensile, transverse-shear, and interlaminar-shear properties of FRP bars subjected to 3 months of accelerated alkaline conditioning at 60°C, as per Canadian Standards Association (CSA) and American Society for Testing and Materials (ASTM) standards. The strength retention and failure of these bars were evaluated as a measurement of the durability and long-term performance of the FRP bars currently available on the market and for quality control by manufacturers. Statistical analysis using independent samples t-test and one-way analysis of variance revealed that the manufacturing parameters have a significant effect on the mechanical characteristics and alkaline resistance of FRP bars. In particular, the results show that the FRP bars manufactured with the same parameters and fiber types but by different fiber manufacturers with different fiber sizings and resin systems produced bars with totally different strength properties and durability performance in an alkaline environment. Vinyl ester resin and silane-sized fiber was the most compatible resin system and produced a more durable glass-FRP bar, while the epoxy resin yielded more durable basalt- and carbon-FRP bars. This paper also describes a procedure for and a criterion of the optimum manufacturing parameters to achieve specific mechanical properties and durability performance with FRP bars.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.214
Teacher spread0.205 · 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.

Study designObservational
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

Citations0
Published2020
Admission routes1
Has abstractyes

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