AN ARTIFICIAL NEURAL NETWORK PREDICTION MODEL FOR FIRE RESISTANCE OF COMPOSITE COLUMNS
Abstract
An artificial neural network prediction model for fire resistance of centrically loaded composite columns exposed to fire from all sides is presented in this paper. Three different types of composite columns, as: totally encased, partially encased and hollow steel sections filled with concrete, as well as ordinary RC columns were analyzed by using the program FIRE. The effects of the shape, the cross sectional dimensions and the intensity of the axial force were analyzed. The results of the performed analyses were used as input parameters for training the neural network prediction model.
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