International Journal of Advance Civil Engineering and Technology ISSN: 3107-7374 (Online)

Authors: Vithal Joshi, B. Suguna Rao, Srikanth M. Naik

Abstract: Earth is facing major environment related problems today such as Global warming and loss of bio-diversity. This brings in the need for Sustainable development, which meets the needs of the present without compromising the ability of future generations to meet theirs. Use of recycled materials in construction, such as recycled aggregates, fly ash, silica fume etc. leads us to less energy consumption in terms of production of cement, transportation etc., less quarrying and thus protection of bio diversity at both quarrying site and dumping sites. But properties of recycled material such as recycled aggregate are substantially different from that of natural aggregates hence prediction of performance of RAC becomes difficult. Here, an attempt is made to predict performance of RAC concrete using modern soft computing tool, i.e. Artificial Neural Network. 136 sets of experimental data from various literature sources were used to train and test the ANN model. The developed ANN model used 14 input parameters and compressive strength at 28 days as output parameter. The results showed that ANN has good potential to be used as a tool to predict strength of sustainable RAC concrete prepared with varying types, sources and ages of recycled aggregate and using industrial wastes.