Optimización de edificios con disipadores de energía pasivos utilizando algoritmos genéticos desarrollados en python 3 adaptados a etabs.

Abstract

This study proposes the optimization of the BRB damper, implemented in a 5-story HA building, using genetic algorithms developed in Python 3 and adapted to ETABS through API tools. The proposed method consists of introducing random BRB capacity curves to the ETABS software through the program developed in Python. The ETABS software executes the Time-History analysis and the Python program retrieves the results of interest and classifies the best curves based on the drifts of the structure. The structure was designed to resist 75% of the forces of the Inelastic Design Spectrum and the BRBs were pre-designed for the remaining 25%. The pre-design BRBs were implemented in the structure and their optimization proceeded. As a result of the optimization, it was found that there is a reduction of 46.91% in the drifts between the structure without BRBs and with optimized BRBs, a decrease in nodal displacements of 48.60% and an increase of 45.19% in the energy dissipated by damping. Similarly, a decrease of 60% of hinges in performance level >CP and 90% of hinges in level between LS-CP is observed.