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ISSN 2063-5346
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Study on Key Factors of Mix Design and Properties of SelfConsolidating Geo-polymer Concrete Using Artificial NeuralNetwork–AReview

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M.Amala,K.Hima Bindu,Dr. M. Siva,Dr.S.Meenakshi Sudarvizhi,Dr.Pala Gireesh Kumar,P.Harshetha
» doi: 10.48047/ecb/2023.12.5.108

Abstract

Toovercomethechallengeofcompactionofgeopolymerconcretecausedbyitshighviscousnature,Self-consolidating Geopolymer Concrete (SCGC) has developed those flows and compacts by its own weight, avoidingthe requirement for additional compaction. The base materials used in SCGC are wastes like pulverized fuel ash,Ground Granulated Blast Furnace Slag (GGBFS), micro silica, limestone fines, rice husk ash, etc. produced fromvariousindustries,whichreactswithanalkalineactivatorsolution.Thisarticlereviewsvariousfactorsandconditionsthat affect the properties of SCGC that are based on different combinations of material bases. To determine variableslike the ideal temperature, percentage of super plasticizers, extra water, aggregate size, molarity of NaOH, ratio ofalkalineactivator,andquantityofbindermaterialstobeworked,athoroughanalysisofthemechanicalanddurabilitycharacteristics of SCGC is conducted. The results obtained from these experiments conducted to find out themechanical and durability characteristics are compared as to establish inferences and effectively comprehend thebehaviourofconcrete.Inadditiontotheassessmentbasedonexperiments,thepossibilityofusinganartificialneuralnetwork inordertoarriveatthe design mix andpredictthepropertiesofSCGCisalsodiscussed in thispaper.

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