Optimization of CH content of ternary cementitious systems and its prediction using artificial neural networks

Author(s): M. Iqbal Khan
Paper category: conference
Book title: Microstructural-related Durability of Cementitious Composites
Editor(s): Guang Ye, K. van Breugel, Wei Sun and Changwen Miao
Print ISBN: 978-2-35158-129-2
e-ISBN: 978-2-35158-123-0
Publisher: RILEM Publications SARL
Publication year: 2009
Pages: 116 - 124
Total Pages: 9
Language: English

Abstract: Hydration of cement constituents brings about setting and hardening of cement. It involves chemical reactions of individual components with water. This paper presents the application of artificial neural networks for the prediction of hydration of high strength concrete. The progress of hydration was monitored by measuring the amount of CH content at various ages using TGA on cement paste incorporating fly ash up to 40% and silica fume up to 15% as partial cement replacements for the preparation of various combinations of binary and ternary blended systems. The interactive effect of fly ash and silica fume on CH content is reported. Based on the experimentally obtained results, the applicability of artificial neural network for
the prediction of hydration using artificial neural networks has a good correlation between the experimentally obtained values. Therefore, it is possible to predict hydration of high strength concrete using artificial neural networks.

Online publication: 2012-05-16
Publication Type: full_text
Public price (Euros): 0.00