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Record W3134734419 · doi:10.11159/ijci.2021.009

Effect of Fly Ash Additive on Mechanical Properties of Concrete

2021· article· en· W3134734419 on OpenAlexvenueno aff
M Conhyea, R Goodary

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2021
Typearticle
Languageen
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsnot available
Fundersnot available
KeywordsFly ashEnvironmental scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The aim of this research is to investigate the effect of fly ash, used as partial replacement to cement CEM I 42.5N, on the properties of fresh and hardened concrete. Fly ash, acquired from a local Thermal Energy Operations industry, based on the island of Mauritius is used to prepare various trial mixes namely FA5, FA10, FA15, FA20, FA25, FA30, FA40 and FA50 with partial replacement of cement by 5%, 10%,15%, 20%,25%, 30% , 40% and 50% of fly ash respectively. The behaviour and strength properties of the samples have been compared to an equivalent mix of plain cement concrete -FA0. At first the tests have been performed on mortar specimens to establish the optimum amount of fly ash which yields maximum compressive strength. As such, samples are prepared from 9 different mixes by substituting only cement by Fly Ash, keeping the total amount of binder constant. The cement, fly Ash, sand and water are mixed together in compliance with prevailing standards -EN 196-1. Mortar samples are cured and matured at 20C. Results show that 15% fly ash replacement of cement yields a maximum compressive strength of 42.5 MPa equating to CEM II 42.5 equivalent strength. Fly Ash with LOI 5% is then used to prepare concrete samples. Concrete of grade 25 has been selected for testing activities to comply with its high demand in Mauritius, i.e. 60% of the local market. Tests are performed on cubes for each trial mix to determine the compressive and flexural strengths respectively after 2, 7 and 28 days. Compressive and Flexural strengths are found to vary in the range of 10.3 -33.1 MPa and 0 -9 MPa respectively for the said grade 25 concrete containing 263.5 Kg of cement and 46.5 Kg of fly ash per m3 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 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 score0.065
Threshold uncertainty score0.305

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 head0.243
Teacher spread0.233 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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