loading page

ANN-based Fatigue Strength of Concrete Under Compression
  • Miguel Abambres ,
  • Lantsoght E
Miguel Abambres
Num3ros, Num3ros

Corresponding Author:[email protected]

Author Profile
Lantsoght E
Author Profile


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.
12 Mar 2024Submitted to TechRxiv
19 Mar 2024Published in TechRxiv
18 Nov 2019Published in Materials volume 12 issue 22 on pages 3787. 10.3390/ma12223787