Open AccessDevelopment of Non Destructive Techniques in Nano Composite Concrete Specimen Using Software Analysis
Author(s) -
Arthi Jayaraman,
N. Sathyakumar,
S Dhivyabharathi
Publication year - 2019
Publication title -
international journal of chemtech research
Language(s) - English
Resource type - Journals
eISSN - 2455-9555
pISSN - 0974-4290
DOI - 10.20902/ijctr.2019.120612
Subject(s) - artificial neural network , compressive strength , portland cement , fuzzy logic , software , nano , cement , materials science , calcium hydroxide , experimental data , composite material , computer science , structural engineering , mathematics , engineering , machine learning , artificial intelligence , statistics , chemical engineering , programming language
This paper presents to study the strength of hardened concrete by software analysisand made comparison with the experimental result. Artificial Neural Network (ANN) andFuzzy logic is one of the popular testing method used in recent days. The paper focuses ondetermination of strength of grade (M40) concrete of different mixes in which ordinaryportland cement is replaced by Nano silica, Nano calcium carbonate and Nano calciumhydroxide of 2%, 4%, 6% and 8% using Artificial neural network and fuzzy. Artificial NeuralNetwork Model and fuzzy model is constructed and the compressive strength of concrete ispredicted by considering specific concrete properties as input variables. Experimental dataresult of these mixes were obtained by testing and is compared with software result. The resultshows that ANN and fuzzy are suitable model and have high potential to predict compressivestrength and predicts good result when compared to experimental result