Strength Prediction of Geopolymer Concrete using ANN
A. Siva Krishna1, V. Ranga Rao2
1A. Siva Krishna, Department of Civil Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
2V. Ranga Rao, Associate Professor, Department of Civil Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 03 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript Published on 28 May 2019 | PP: 661-667 | Volume-7 Issue-6C2 April 2019 | Retrieval Number: F11220476C219/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Geopolymer concrete usage is suddenly increasing across the globe due to the inventions in this area. Various types of research works are being conducted by researchers. The molar concentration of the geopolymer solution will have an effect on its strength. Finding the optimum value through experimentation is a tedious task and predicting the strength variations need laborious calculations. Soft computing techniques make this work easy. Artificial Neuron Network (ANN) is an effective soft computing tool to predict the strength variation that may occur due to the variation in concentration of geopolymer solution. In this work, ANN is used to predict strength with molar concentration variation. A good fit was found between experimental and predicted values.
Keywords: Artificial Neural Network, Strength Prediction, Geo polymer Concrete.
Scope of the Article: Concrete Structures