Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
260651 | Construction and Building Materials | 2009 | 12 Pages |
Abstract
An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Civil and Structural Engineering
Authors
B.K. Raghu Prasad, Hamid Eskandari, B.V. Venkatarama Reddy,