Citation

Al-Khaleefi AM, Terro MJ, Alex AP, Wang Y. Fire Safety J. 2002; 37(4): 339-352.

Copyright

(Copyright © 2002, Elsevier Publishing)

DOI

unavailable

PMID

unavailable

Abstract

A functional relationship between the fire resistance of a concrete filled steel column and the parameters which cause the fire resistance is represented using an artificial neural network. Experimental data obtained from previous laboratory fire tests are used for training the neural network model. The model predicted values are compared with actual test results. The results indicate that the model can predict the fire resistance with adequate accuracy required for practical design purpose. The developed neutral network can be used to predict the fire resistance of similar columns under fire by observing various factors influencing the resistance such as: (a) structural factors, (b) material factors, and (c) loading conditions. The structural engineer is required to provide the magnitude of these influencing factors as inputs to the neural network and the network will predict the fire resistance, based on the combined effect of these factors. This system can be used by structural engineers to predict the resistance of fire in similar concrete filled steel columns without conducting costly fire tests, by using the known parameters such as column dimensions, column height, and loading conditions.