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Record W4376288163 · doi:10.18280/rcma.330203

Assessment of the PVC Waste Addition Effect on the Concrete Mechanical Performance

2023· article· fr· W4376288163 on OpenAlexvenueno aff
Mourad Boutlikht, Kamel Hebbache, Abdellah Douadi, Seifeddine Tabchouche

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2023
Typearticle
Languagefr
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsWaste managementMaterials scienceComposite materialEngineering

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate the possibility of using the polyvinyl chloride (PVC) wastes as a concrete manufacturing material without pre-treatment.The purpose is also to contribute for restricting environmental pollution and exploitation of natural resources, through the stabilization and the solidification of PVC wastes in concrete.The aim of this experimental study is to evaluate experimentally the fresh and cured properties of PVC concrete based in comparison with ordinary concrete (OC).This study consists in collecting PVC waste, especially the used PVC pipes rejected in nature, and incorporate it into concrete by substitution of sand with different volume ratios (5%, 10% and 15%).In this study, two different shapes (Fiber and Fine) of PVC were considered.According to the test results, the addition of PVC waste in concrete as a partial replacement for natural sand conducts to decrease the workability of fresh concrete.It was noticed that, the concrete with PVC fiber shows a lower workability comparatively with fine PVC concrete.It was also observed that the PVC fiber improves the concrete compressive strength.It increases with increasing the replacement ratio of PVC waste.However, the increase in the ratio of fine PVC leads to a decrease in compressive strength.The better mechanical performance factor (MPF) was obtained for concrete mixes with high PVC fiber and moderate PVC fine ratios.The collected outcomes would contribute to helpful information for recycling PVC waste in concrete mixes.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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 head0.033
GPT teacher head0.260
Teacher spread0.227 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicMicroplastics and Plastic PollutionFrench-language works237,207