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Record W3199283464 · doi:10.1139/cjce-2021-0258

Utilization of granite powder and glass powder in reactive powder concrete: assessment of strength and long-term durability properties

2021· article· en· W3199283464 on OpenAlexvenueno aff
V. Kannan, M. Sophia

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
Fundersnot available
KeywordsSorptivityDurabilityMaterials scienceAbsorption of waterCementQuartzBrineComposite materialElectrical resistivity and conductivityMetallurgyChemistry

Abstract

fetched live from OpenAlex

This paper aims to assess the mechanical and long-term durability performance of reactive powder concrete (RPC) containing granite powder (GrP) as cement replacement and waste glass powder (GP) as quartz sand replacement. The workability and mechanical behaviour of RPC containing various proportions of GrP and GP are assessed for different water/binder (w/b) ratios (0.3, 0.35, 0.4, and 0.45). The water resistance and tightness of RPC are measured by monitoring the electrical resistivity, water absorption, sorptivity, and chloride migration over a one-year period. Results reveal that substitution of GrP and GP at optimum levels of 15% and 30% respectively enhances the performance of RPC with the achievement of satisfiable workability at a 0.35 w/b ratio. A significant increase in the resistance towards chloride penetration and electrical resistivity was also observed with increasing ages. Thus, glass powder and granite powder can be considered as alternative construction materials providing economical and ecological efficiency.

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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.243
Teacher spread0.222 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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