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Record W4415151081 · doi:10.11159/ijci.2025.016

Ground Recycled Glass to Improve the Compressive Strength of Concrete

2025· article· en· W4415151081 on OpenAlexvenueno aff
Kevin Ccente, Carlos Eyzaguirre

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2025
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCompressive strengthCompression (physics)Deformation (meteorology)Ultimate tensile strengthWelding

Abstract

fetched live from OpenAlex

This paper explores the use of recycled ground glass as a partial substitute for sand in concrete mixtures, aiming to enhance its mechanical properties, specifically compressive and flexural strength.Mixtures with glass replacements of 15%, 20%, and 25% were developed and tested, evaluating their performance at 7, 14, and 28 days.Experimental results indicate that using 15% ground glass increases compressive strength by 4.91% compared to standard concrete and improves workability without significantly affecting cohesion.In contrast, higher glass percentages increase the mixture's porosity, reducing its density and compressive strength.Flexural strength tests revealed that the 15% replacement achieved the best performance, with an increase of 2% compared to the control mix, while the 20% and 25% substitutions showed slight reductions in flexural capacity due to increased brittleness.These findings suggest that a moderate incorporation of ground glass not only enhances compressive behavior but also slightly improves flexural performance, making it suitable for structural applications with sustainability criteria.Additionally, an economic analysis was performed, showing that the use of recycled ground glass as a partial substitute for sand can reduce material costs in optimal replacement proportions, reinforcing the viability of this approach for practical applications.The research concludes that incorporating ground glass is a sustainable and economically feasible alternative, as it promotes waste reuse, reduces the demand for natural sand, and improves the overall mechanical performance of concrete.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0020.000

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 head0.231
Teacher spread0.228 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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Same venueInternational Journal of Civil InfrastructureSame topicRecycled Aggregate Concrete PerformanceFrench-language works237,207