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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/7983
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dc.contributor.authorLahoti, Mukund-
dc.date.accessioned2022-12-20T10:43:11Z-
dc.date.available2022-12-20T10:43:11Z-
dc.date.issued2017-10-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0272884217312087-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/7983-
dc.description.abstractGeopolymer is a promising alternative binder to Portland cement. However, the importance of mix design parameters affecting the mechanical properties of geopolymer has yet to be quantitatively assessed. This work evaluates the significance of the four common mix design parameters, namely Si/Al (molar ratio), water/solids (mass ratio), Al/Na (molar ratio) and H2O/Na2O (molar ratio), in determining compressive strength of metakaolin-based geopolymers through experiments and statistical analyses. In addition, machine learning-based classifiers were engaged for strength predictions. Results showed that Si/Al ratio is the most significant parameter followed by Al/Na ratio. Unlike ordinary Portland cement system, water/solids ratio is not the chief factor governing strength of metakaolin-based geopolymers. Machine learning-based classifiers were able to predict the compressive strength with high precision. The strength predictions can potentially guide preliminary mix proportioning of metakaolin-based geopolymers to achieve required strength grade without going through tedious (trial and error) mix formulation.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCivil Engineeringen_US
dc.subjectElectron microscopyen_US
dc.subjectPorosityen_US
dc.subjectStrengthen_US
dc.subjectAttribute evaluationen_US
dc.titleMix design factors and strength prediction of metakaolin-based geopolymeren_US
dc.typeArticleen_US
Appears in Collections:Department of Civil Engineering

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