Use of the Artificial Neural Networks to Estimate the DRF for Eurocode 8

  • Baizid Benahmed
  • Malek Hamoutenne


The damping reduction factor (DRF) is used in earthquake engineering in order to estimate the seismic response of buildings with high damping ratio from the one which has damping ratio equal to 5%. Many expressions were given to this factor as a function of different parameters in literature. The concern of these formulations is to find a simple and a reliable formulation, which presents a challenge. This is the major reason to look for a new simple method to estimate the DRF values with a good approximation. The primary objective of this work is to develop a new method to estimate the DRF using Artificial Neural Networks (ANN). This method is developed for the seismic Eurocode 8 (EC8). In a first step, seeking for sets of ground motions records that gives as average the best approximation of the target spectra of EC 8. Afterward, those records are used to estimates the exact response spectra and the DRF values in function of damping ratio ξ and period (T) through a time History Analysis. In a second step, those results are used as neural networks database to predict the DRF in function of ξ and T. The proposed approach is original and the associated results are interesting and promising.

Keywords: ground motions, Damping Reduction Factor (DRF), Artificial Neural Networks (ANN), Eurocode 8
Published online
How to Cite
Benahmed, B., & Hamoutenne, M. (2018). Use of the Artificial Neural Networks to Estimate the DRF for Eurocode 8. Periodica Polytechnica Civil Engineering, 62(2), 470-479.
Research Article