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Record W4400235031 · doi:10.11159/iccste24.237

Setting Time and Workability of Geopolymerized Fly Ash-Phosphogypsum Paste and Mortar

2024· article· en· W4400235031 on OpenAlexvenueno aff
Jabulani Matsimbe, Megersa Olumana Dinka, David O. Olukanni, Innocent Musonda

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsnot available
FundersAfrican UnionEuropean Commission
KeywordsPhosphogypsumFly ashMortarWaste managementEnvironmental scienceMaterials scienceComposite materialEngineeringRaw materialChemistry

Abstract

fetched live from OpenAlex

Geopolymer is no longer viewed as a concept for a greener society but rather as a pragmatic solution for reducing CO2 emissions in the construction industry. It is commonly produced using industrial waste materials such as fly ash (FA) and phosphogypsum (PG). Globally, FA has an estimated annual production of around 1 billion tonnes and that of phosphogypsum is around 300 million tonnes, of which utilization stands at 50% and 15% of the total generated, respectively [1]. Geopolymers have been extensively studied as an alternative to ordinary Portland Cement (OPC) [2], [3] but to date, no study has been done to investigate the setting time and workability of geopolymerized fly ash-phosphogypsum paste and mortar. This research investigates the setting time and workability of geopolymerized fly ash-phosphogypsum paste (GPP) and mortar (GPM) using a Vicat needle procedure per ASTM C191 and the flow table test per ASTM C1437, respectively. The materials used were PG, Class F FA, silica sand, NaOH pellets of 99% purity, and Na2SiO3 solution of the composition Na2O = 8.3%, SiO2 = 27.7%, H2O = 64%, and Ms (SiO2/Na2O) = 3.34. The dissolution of NaOH pellets in water is an exothermic process [4] therefore the prepared NaOH solution was kept in a sealed glass bottle for 24 hours at room temperature to allow sufficient cooling before mixing with the Na2SiO3 solution. The specimens were prepared at 10M NaOH + Na2SiO3 Ms of 3.34, Na2SiO3/ NaOH ratio of 1.5, Alkaline Liquid/Precursor ratio of 0.4, Binder/Aggregate ratio of 1.0, and varying PG at 10 wt% increments. As per ASTM C305 for mixing pastes and mortars, the preparation of the specimens started with dry mixing the FA with PG in a conventional pan mixer for 3 minutes, followed by the gradual addition of alkaline solution and wet mixing for 5 minutes. Soon after wet mixing, the manufactured paste and mortar were tested for setting time and workability. It was found that an increase in the PG wt% led to a decrease and/or acceleration in the initial setting time (INSET) and final setting time (FINSET) attributed to the rapid dissolution of Ca2+ in low alkaline concentrations outnumbering that of Al3+ and Si4+ and thus forming ettringite and C-A-S-H gel that facilitates hardening shortening the setting time [5], [6]. The INSET of GPP decreased from 37 min (at 10wt% PG) to 27 min (at 30 wt% PG) while the FINSET of GPP decreased from 155 min (at 10wt% PG) to 125 min (at 30 wt% PG). The INSET of GPM decreased from 29 min (at 10wt% PG) to 23 min (at 30 wt% PG) while the FINSET of GPM decreased from 142 min (at 10wt% PG) to 113 min (at 30 wt% PG). Furthermore, the workability of GPP and GPM decreased with an increase in PG wt% attributed to faster hydration activity, accelerated setting, and increased viscosity. The workability of GPP decreased from 176 mm (at 10 wt% PG) to 138 mm (at 30 wt% PG) while that of GPM decreased from 137 mm (at 10 wt% PG) to 112 mm (at 30 wt% PG). The development of GPP and GPM offers a sustainable circularity construction solution to minimize OPC usage and prevent the disposal of FA and PG in landfills. Future research should investigate the mechanical properties of GPP and GPM.

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 score0.821
Threshold uncertainty score0.404

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Civil, Structural and Transportation EngineeringSame topicTunneling and Rock MechanicsFrench-language works237,207