Integration of digital models and real data for the forecast and validation of seismic behavior of tall building

This research evaluates the reliability of numerical methods to analyse skyscrapers subjected to extreme actions based on ETABS model, that model have ten story tower excited by an earthquake of magnitude MW 9.5 the research combines finite element modeling, model analyses and verification of inter-stage deviation complemented by a review of artificial intelligence methods based on neural networks for the automatic characterization of building from urban images, the results show participatory mass ratios close to 0.9 on short periods, indicating a generally rigid and well mobilized structure, but also reveal a very high maximum drift ratio at the last level in one direction, sign of unevenness in rigidity and possible concentration of damage, strengthening strategies are proposed ( additional sails, increase in sections, consideration of the soil structure interaction) in order to bring the response within the regulatory limits, the research concludes that the numerical model calibrated and validated by real data and complemented by probabilistic and AI approaches provides is a good approaches for skyscrapers analyses.