Paper Title:
Optimum Mixture Design of Bottom Ash Based Alkali-Activated Mortar Using Artificial Neural Networks
  Abstract

Bottom ash based alkali-activated mortar is prepared by incorporating sodium hydroxide and sodium silicate with some additional water if needed, and is activated with temperature curing. This research was conducted to derive an optimum mixture design of the bottom ash based alkali-activated mortar. The experimental studies were first performed to estimate the effect of the added water content, alkali activator to bottom ash ratio, sodium silicate to sodium hydroxide ratio as well as curing temperature on workability and strength. In order to optimize the mix proportion, based on the experimental results, artificial neural networks were introduced.

  Info
Periodical
Key Engineering Materials (Volumes 452-453)
Edited by
A. Saimoto and M.H. Aliabadi
Pages
733-736
DOI
10.4028/www.scientific.net/KEM.452-453.733
Citation
S. T. Kang, H. J. Kang, G. S. Ryu, G. T. Koh, J. H. Lee, "Optimum Mixture Design of Bottom Ash Based Alkali-Activated Mortar Using Artificial Neural Networks ", Key Engineering Materials, Vols. 452-453, pp. 733-736, 2011
Online since
November 2010
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$32.00
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