ANN Modeling to study strength loss of Fly Ash Concrete against Long term Sulphate Attack

This paper presents the findings from experiments to investigate the effect of fly ash addition in concrete as partial cement replacement on compressive strength under prolonged sulphate exposure. Further, an artificial neural network (ANN) model has been developed to predict the compressive strength of the concrete at varied fly ash replacement level, water curing days and sulphate exposure periods. Cement in concrete has been replaced by fly ash in two levels of replacements such as 25% (Low) and 40% (High). The 28, 90 and 180 days water cured samples of control concrete (CC), Low Fly ash Concrete (LFC) and High Fly ash concrete (HFC) have been subjected to 5% sodium sulphate solution for chemical exposure periods of 6, 12, 15, 18 and 24 months respectively. A total number of 162 concrete cubes of CC, LFC and HFC have been cast towards the comparative assessment of the effect. The experimental data have been used to train the neural network. The predicted data and experimental data display a close match. (C) 2018 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials and Manufacturing Applications [IConAMMA 2017].