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Record W2621129564 · doi:10.1080/21650373.2017.1334601

Performance of concrete with blended binders in ammonium-sulphate solution

2017· article· en· W2621129564 on OpenAlexafffund
Mahmud Amin, M. T. Bassuoni

Bibliographic record

VenueJournal of Sustainable Cement-Based Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsSilica fumeFly ashPortland cementMaterials scienceCementCementitiousAmmoniumSulfateAmmonium sulfateComposite materialMetallurgyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Concrete elements in agricultural, wastewater treatment, mining, and industrial applications can be vulnerable to chemical attack by ammonium-based solutions. In particular, ammonium sulfate (commonly used as a fertilizer) is extremely deleterious to concrete. This is due to its dual acid–sulfate action, which may disintegrate the hydrated cement paste to various levels based on the prevailing exposure conditions and key mixture design parameters of concrete. The aim of this study was to investigate the response, in terms of physico-mechanical and microstructural features, of concrete comprising different types of cement (general use [GU] or Portland limestone cement [PLC]) with various combinations of supplementary cementitious materials (SCMs: fly ash, silica fume, and nanosilica) to a severe ammonium sulfate exposure. The study comprised 12 months of immersing test specimens in 5% ammonium sulfate solutions with a pH level of 6.0–8.0. The results revealed that the type of binder along with the dosage and nature of SCMs dictated different modes and levels of deterioration, and consequently the physico-mechanical trends of concrete were characterized by softening with (single binders) or without (blended binders) significant expansion. PLC may slightly improve the resistance of concrete to ammonium sulfate attack, whereas among the blended binders tested, binary binders comprising 5% silica fume, 5% nanosilica, or 30% fly ash improved the resistance of concrete to this type of chemical attack.

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)0.001
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 score0.003
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.240
Teacher spread0.226 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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