WIT Press


Application Of Artificial Neural Network For Dimensional Stability Of Repair Materials Under Local Hot Weather

Price

Free (open access)

Paper DOI

10.2495/CMEM130211

Volume

55

Pages

12

Page Range

263 - 274

Published

2013

Size

257 kb

Author(s)

M. I. Khan

Abstract

In Saudi Arabia, the majority of concrete structures constructed more than three decades ago suffer because of lack of quality control and severe weather conditions. Concrete structures are prone to deterioration due to the very hot and harsh environmental conditions. In this paper, six candidate materials are reported. Mixture proportions, mixing and curing for all selected materials were employed as per the recommendations suggested by the manufacturer. Based on the experimentally obtained results, the applicability of an artificial neural network for the prediction of shrinkage has been established. The predicted values obtained using artificial neural networks have a good correlation between the experimentally obtained values. Therefore, it is possible to avoid shrinkage of repair materials using artificial neural networks. Keywords: repair materials, dimensional stability, neural network, hot weather.

Keywords

Keywords: repair materials, dimensional stability, neural network, hot weather.