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Record W3035209978 · doi:10.18280/acsm.440204

Experimental Analysis on Mechanical Performance of Recycled Concrete Made from Polypropylene Fiber and Artificial Sand

2020· article· en· W3035209978 on OpenAlexvenueno aff
Huan Luo, Furong Ma, Qian Yang

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2020
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
FundersGuangxi University
KeywordsPolypropyleneMaterials scienceComposite materialFiber

Abstract

fetched live from OpenAlex

This paper aims to disclose the working performance and mechanical performance of recycled concrete made from polypropylene fiber and artificial sand (P-RCAS).Taking fiber content and concrete strength as variables, a total of 90 P-RCAS cubes and prisms were designed and prepared for axial loading tests.The working performance of the P-RCAS was tested, the failure process and failure mode of the specimens were observed, and the compressive strengths of cubs and prisms were measured.Moreover, the authors probed deep into how fiber content affect the working performance and mechanical performance of the P-RCAS.The results show that adding polypropylene fiber into the artificial sand recycled concrete (RCAS) can produce concrete with good workability; the additional fibers help to enhance the compressive strength of RCAS specimens on all strength levels, but the enhancement was insignificantly for specimens on high strength levels.Finally, the test data were used to fit the calculation formulas for fiber content, water-cement ratio, and compressive strength, as well as the relationship between axial compressive strength and cube compressive strength.The research results provide reference for further research and engineering application of the RCAS.

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 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 score0.362
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.246
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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAnnales de Chimie Science des MatériauxSame topicRecycled Aggregate Concrete PerformanceFrench-language works237,207