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Use of Polymeric Fibers in the Development of Semilightweight Self-Consolidating Concrete Containing Expanded Slate

2020· article· en· W3008248640 on OpenAlexaff
Ahmed T. Omar, Mohamed K. Ismail, Assem A. A. Hassan

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMaterials scienceComposite materialPolypropyleneAggregate (composite)Flexural strengthPolyvinyl alcoholFiberSelf-consolidating concreteCompressive strength

Abstract

fetched live from OpenAlex

This paper aims to evaluate and optimize a number of semilightweight self-consolidating concrete (SLWSCC) mixtures containing coarse and fine aggregates, lightweight expanded slate, and reinforced with different types of polymeric fiber. The fibers used were 8 and 12 mm polyvinyl alcohol (PVA8 and PVA12), and 19 mm polypropylene (PP19). The developed mixtures included different binder contents (550 and 600 kg/m3), fiber volumes (0.3% and 0.5%), and coarse-to-fine (C/F) aggregate ratios (0.7 and 1.0). Two normal-weight self-consolidating concrete (NWSCC) mixtures made with fine and coarse crushed granite aggregates also were tested in this investigation for comparison. Although the use of polymeric fibers negatively affected the fresh properties of the mixture, it was possible to develop successful SLWSCC mixtures with significantly improved flexural strength using up to 0.5% fibers. SLWSCC mixtures with shorter fibers (PVA8) had better fresh properties and strengths compared to mixtures with longer fibers (PVA12 and PP19). A minimum of 550 kg/m3 binder content was required to develop SLWSCC mixtures with acceptable self-compactability. However, using 600 kg/m3 binder content contributed to improving the fresh properties of the mixture, which allowed using a higher content of lightweight expanded slate aggregate, achieving a further reduction of the mixture density. The results also showed that unlike the lightweight coarse aggregates, the use of lightweight fine aggregates helped to develop mixtures with higher flowability, passing ability, and strengths.

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 score0.038
Threshold uncertainty score0.825

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)0.0000.000

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 head0.223
Teacher spread0.195 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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