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Record W1773252879 · doi:10.1520/acem20120014

Effect of UV and UV–Ozone Treatment of Polyolefin Fibers on Toughness of Fiber Concrete Composite

2013· article· en· W1773252879 on OpenAlexaff
Pouria Payrow, Michelle Nokken, D. Banu, Rolf Schmidt, Christine DeWolf, D. Feldman

Bibliographic record

VenueAdvances in Civil Engineering Materials · 2013
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials sciencePolyolefinComposite materialFlexural strengthComposite numberToughnessFiberOzoneContact angleUltravioletIrradiationDeformation (meteorology)Layer (electronics)Chemistry

Abstract

fetched live from OpenAlex

Abstract Ultraviolet (UV) irradiation and a combination of UV irradiation and ozone treatment of polyolefin fibers were investigated for possible improvement of mechanical properties in concrete composites. In both treatment methods, various fiber exposure durations were used, and surface modification was monitored by measuring the water contact angle. Untreated and treated fibers were added to concrete at 0.32 % by volume, and the specimens were tested for flexural strength according to ASTM International specifications. Fiber surface treatment by UV alone was found to be an unattractive technique based on the results of flexural tests and contact angle measurements. Ten minutes of UV and ozone surface treatment of fibers was found to improve the composite peak stress by 11 % and the toughness by 4 %; longer periods of exposure led to lower flexural strength results, perhaps as a result of fiber deformation or degradation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2013
Admission routes1
Has abstractyes

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