Development of a predictive optimization model for the compressive strength of sodium activated fly ash based geopolymer pastes

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@Article{Fillenwarth:2015:Fuel,

• author = "Brian A. Fillenwarth and Shankar M. L. Sastry",
• title = "Development of a predictive optimization model for the compressive strength of sodium activated fly ash based geopolymer pastes",
• journal = "Fuel",
• volume = "147",
• pages = "141--146",
• year = "2015",
• ISSN = "0016-2361",
• DOI = "doi:10.1016/j.fuel.2015.01.029",
• URL = "http://www.sciencedirect.com/science/article/pii/S0016236115000435",
• abstract = "As concerns about global CO2 emissions grow, there exists a need for widespread commercialisation of lower emission building materials such as geopolymers. The commercialisation of geopolymers is currently impeded by the high variability of the materials used for their synthesis and limited knowledge of the interrelationships between mix design variables. To overcome these barriers, this work demonstrates a relationship between the compressive strength and the chemical design variables derived from experimental data using genetic programming. The developed model indicates the main chemical factors responsible for the compressive strength of sodium activated geopolymers are the contents of Na2O, reactive SiO2, and H2O. The contents of reactive Al2O3 and CaO were found to not have a significant impact on the compressive strength. The optimisation model is shown to predict the compressive strength of fully cured sodium activated fly ash based geopolymer pastes from their chemical composition to within 6.60 MPa.",
• keywords = "genetic algorithms, genetic programming, Alkali activated cement, Geopolymer paste, Compressive strength, Fly ash, Predictive optimisation model",

}

Genetic Programming entries for Brian A Fillenwarth Shankar M L Sastry

Citations