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Record W4400235334 · doi:10.11159/iccste24.199

Properties of Geopolymer Concrete Made With Recycled Concrete Aggregates and Glass Fibers

2024· article· en· W4400235334 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
FundersUnited Arab Emirates University
KeywordsGeopolymer cementGeopolymerMaterials scienceComposite materialGlass recyclingGlass fiberCompressive strength

Abstract

fetched live from OpenAlex

This research aims to evaluate the workability and compressive strength of geopolymer concrete made with recycled concrete aggregates (RCA) and glass fibers (GF).The ambient-cured geopolymer concrete was prepared using a binder blend of slag and fly ash (3:1) and fine aggregates in the form of desert dune sand.Natural aggregates or RCA served as the coarse aggregates, while sodium silicate and sodium hydroxide formulated the alkaline activator solution.The investigated process parameters included the replacement percentage of natural aggregates with RCA, binder content, amount of additional water (added to the alkaline activator solution), particle size distribution of RCA, and volume fraction of GF.Experimental results indicated that replacing natural aggregates with 100% RCA had an insignificant impact on the workability but reduced the compressive strength by up to 25%.Increasing the binder content from 300 to 450 kg/m 3 in RCA geopolymer concrete reinforced with up to 2% GF, by volume, led to up to 28, 106, and 17% higher workability and 1-and 7-day compressive strengths, respectively.Adding up to 50 kg/m 3 of water increased the workability up to 230 mm while decreasing the compressive strength by up to 22%.Meanwhile, sieving the RCA to remove particles smaller and larger than 4.75 mm and 19 mm, respectively, increased the slump to 210 mm and 1-and 7-day compressive strength by 29 and 35%, correspondingly.The addition of 1 and 2% GF, by volume, decreased the workability by 2 and 9%, respectively, in comparison to the plain RCA geopolymer concrete mix, while the compressive strength was unaffected.Experimental findings highlight the possibility of utilizing RCA as a replacement for natural aggregates in slag-fly ash blended geopolymer concrete reinforced with glass fibers without compromising performance.Such beneficial use of RCA serves as a means of alleviating the adverse environmental impact associated with its disposal.

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.

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 score0.401
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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