MétaCan
Menu
Back to cohort
Record W2998065634 · doi:10.1139/cjce-2019-0524

Mechanical performance of engineered cementitious composites incorporating recycled glass powder

2019· article· en· W2998065634 on OpenAlexafffundvenue
Adeyemi Adesina, Sreekanta Das

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceFly ashComposite materialPortland cementCementitiousFlexural strengthUltimate tensile strengthCompressive strengthComposite numberGlass recyclingCement

Abstract

fetched live from OpenAlex

Engineered cementitious composite (ECC) is conventionally made up of high content fly ash (FA) combined with Portland cement (PC) as a binder. However, the growing call for sustainability is leading to continuous decommissioning of various coal power plants around the world thereby limiting the supply of fly ash available for ECC production. Therefore, it is of high importance to find alternative materials that can be incorporated into ECC as a partial replacement of the conventional binders. This experimental investigation was carried out to investigate the feasibility of incorporating glass powder (GP) as binder into ECC mixtures. The mechanical performance in terms of its compressive, tensile, and flexural properties was evaluated. Results from this study showed that 25% FA can be replaced with GP without any significant reduction in the mechanical performance of ECC mixtures. Microstructural investigations of the mixtures incorporating GP show good bonding between the cementitious matrix and the fibres.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.006
GPT teacher head0.173
Teacher spread0.167 · 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

Citations20
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicInnovative concrete reinforcement materialsFrench-language works237,207