ANN-based Methodology to Determine Dynamic to Static Eccentricity Ratio of Torsionally Coupled Buildings for Site-Specific Earthquakes

Abstract

Although excessive damage of torsionally coupled buildings situated on soil sites has been reported during past earthquakes, no site-specific study is available having depth of soil stratum above rock as a parameter. In this article, an Artificial Neural Network-based methodology to determine dynamic to static eccentricity ratio of torsionally coupled buildings is proposed. Twelve neural networks are developed using 648,000 patterns from the analyses of shear type single-story building models. The methodology is found to be appropriate to determine dynamic to static eccentricity ratio for multi-story uniform, non uniform framed, and shear wall buildings for site-specific earthquake.