“Analysis of CFST using Artificial Neural Network”

Authors

  • Faizan khan , Mohammed Taiyeb , MD Abdullah , MD Khizeer , Dr N S Kumar

Abstract

In this paper we are going to analyse the Concrete filled steel tubes structures behaviour,
characteristics when subjected to bearing capacities, using ANN in MATLAB. Further checking the
efficiency of results by creating diversity in network properties by altering (Hidden layers, neurons etc)
them. A concrete filled steel tubular is a composite material composed of concrete embeded with steel or
vice verse. The interaction between concrete and steel is proven efficient under high bearing capacity with
good plasticity and toughness index. An Artificial Neural Network (ANN) is computing model whose
structure resembles the network structure is similar or can be refered to biological nerve cell, with layers of
connected nodes. Artificial neural network has now become very much reliable in analytical modelling of
structures and it is a sophesticated tool for machine learning. This paper will provides an introduction to
artificial neural network a brief applicability to problems. As we know a neural network can learn from data
and provide us accuracy in our results with less percentage error with the help of hidden layers which are
also called magic box. This paper will further depicts that what is the impact on results observed due to
altering the network (ANN) properties. As said before the predicted results will be compared will
experimental results to depict the efficiency of artificial intelligence in field of civil engineering

Published

2020-04-30

Issue

Section

Articles