This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
Volume 12 article 277 pages: 63-68
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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