Abstract
When concrete is subjected to cycles of compression, its strength is
lower than the statically determined concrete compressive strength. This
reduction is typically expressed as a function of the number of cycles.
In this work, we predict the reduced capacity as function of a given
number of cycles by means of artificial neural networks (ANN). A
203-point experimental dataset gathered from the literature was used.
The proposed ANN model results in a maximum relative error of 5.1% and
a mean counterpart of 1.2% for the whole dataset. It’s shown that the
proposed analytical model outperforms the existing design code
expressions.