Use of Artificial Neural Network in Design of Fly Ash Blended Cement Concrete Mixes
Alok Verm1, Ishita Verma2
1Alok Verma, Professor in Civil Engineering at Delhi Technological University, Delhi India.
2Ishita Verma, Department of civil engineering at Gautam Buddha University.
Manuscript received on 06 August 2019. | Revised Manuscript received on 14 August 2019. | Manuscript published on 30 September 2019. | PP: 4222-4233 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5146098319/2019©BEIESP | DOI: 10.35940/ijrte.C5146.098319
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Abstract: Cement concrete is the most important construction material which is non-homogeneous in nature. Its strength depends on properties of its many constituent materials are diverse in nature. It is important to fix up exact proportions of these materials beforehand so that needed strength in concrete is obtained later on. Sufficient time is needed to check it by making trial mixes of concrete after fixing up the proportions by theoretical calculations and testing these trial mixes after 28 days. In this duration concreting work may be held up in the absence of a final approved mix in terms of quantities of various constituents of concrete. Use of artificial neural networks (ANNs) for the checking of design composition of fly ash blended cement concrete mixes which were designed as per Indian standard guidelines has been made. Prediction of strength of such mixes at a later date by ANN has also been explored in this study. Prediction results of ANNs come close to experimental values and reinforce the utility of ANNs in the area of use of civil engineering materials for improving efficiency in construction.
Keywords: ANN, Fly ash Concrete, Mix Design, Prediction.
Scope of the Article: Application Artificial Intelligence and machine learning in the Field of Network and Database