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Optimization of Pervious Geopolymer Concrete Using TOPSIS-Based Taguchi Method

Author

Listed:
  • Faiz Habib Anwar

    (Department of Civil and Environmental Engineering, UAE University, Al Ain P.O. Box 15551, United Arab Emirates)

  • Hilal El-Hassan

    (Department of Civil and Environmental Engineering, UAE University, Al Ain P.O. Box 15551, United Arab Emirates)

  • Mohamed Hamouda

    (Department of Civil and Environmental Engineering, UAE University, Al Ain P.O. Box 15551, United Arab Emirates)

  • Abdulkader El-Mir

    (Department of Civil and Environmental Engineering, UAE University, Al Ain P.O. Box 15551, United Arab Emirates)

  • Safa Mohammed

    (Department of Civil and Environmental Engineering, UAE University, Al Ain P.O. Box 15551, United Arab Emirates)

  • Kim Hung Mo

    (Department of Civil Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

Abstract

This paper evaluates the effect of mix design parameters on the mechanical, hydraulic, and durability properties of pervious geopolymer concrete (PGC) made with a 3:1 blend of granulated blast furnace slag (GBFS) and fly ash (FA). A total of nine PGC mixtures were designed using the Taguchi method, considering four factors, each at three levels, namely, the binder content, dune sand addition, alkaline-activator solution-to-binder ratio (AAS/B), and sodium hydroxide (SH) molarity. The quality criteria were the compressive strength, permeability, and abrasion resistance. The Taguchi and TOPSIS methods were adopted to determine the signal-to-noise (S/N) ratios and to optimize the mixture proportions for superior performance. The optimum mix for the scenarios with a compressive strength and abrasion resistance at the highest weights was composed of a binder content of 500 kg/m 3 , dune sand addition of 20%, AAS/B of 0.60, and SH molarity of 12 M. Meanwhile, the optimum mix for the permeability-dominant scenario included a 400 kg/m 3 of binder content, 0% of dune sand addition, 0.60 of AAS/B, and 12 M of SH molarity. For a balanced performance scenario (i.e., equal weights for the responses), the optimum mix was similar to the permeability scenario with the exception of a 10% dune sand addition. An ANOVA showed that the binder content and dune sand addition had the highest contribution toward all the quality criteria. Multivariable regression models were established to predict the performance of the PGC using the mix design factors. Experimental research findings serve as a guide for optimizing the production of PGC with a superior performance while conducting minimal experiments.

Suggested Citation

  • Faiz Habib Anwar & Hilal El-Hassan & Mohamed Hamouda & Abdulkader El-Mir & Safa Mohammed & Kim Hung Mo, 2022. "Optimization of Pervious Geopolymer Concrete Using TOPSIS-Based Taguchi Method," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8767-:d:865270
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    References listed on IDEAS

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    1. Abdulkader El-Mir & Hilal El-Hassan & Amr El-Dieb & Abdelrahman Alsallamin, 2022. "Development and Optimization of Geopolymers Made with Desert Dune Sand and Blast Furnace Slag," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
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    Cited by:

    1. Sunghun Kim & Youngjin Park & Seungbeom Yoo & Ocktaeck Lim & Bernike Febriana Samosir, 2023. "Development of Machine Learning Algorithms for Application in Major Performance Enhancement in the Selective Catalytic Reduction (SCR) System," Sustainability, MDPI, vol. 15(9), pages 1-20, April.

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