Applying Genetic Algorithm to estimate the behavior factor of EBF steel frames under pulse-type near-fault earthquakes, performance level approach

Abstract

The most important feature of the behavior factor is that it allows the structural designer, to be able to evaluate the structural seismic demand, using an elastic analysis, based on force-based principles quickly. In seismic codes such as the 2800Standard, this coefficient is merely dependent on the type of lateral resistance system and is introduced with a fixed number. However, there is a relationship between the behavior factor, ductility (performance level), structural geometric properties, and type of earthquake (near and far). The main purpose of this paper is to establish an accurate correlation between the geometrical characteristics of the structure, performance level and the behavior factor in eccentrically steel frames, under earthquakes near-fault. For this purpose, genetic algorithm is used. Initially a wide database consisting of 12960 data with 3-, 6-, 9-, 12-, 15- and 20- stories, 3 column stiffness types, and 3 brace slenderness types were designed, and analyzed under 20 pulse-type near-fault earthquakes for 4 different performance levels. To generate the proposed relation, 7,500 training data in the form of genetic optimization algorithm were used. To validate the proposed relationship, 2,500 test data were used to calculate the mean squared error of the relationship in the fitness function. The results of the correlation, shows accuracy of proposed coefficients. Also, the comparison of the response of maximum inelastic displacement of 5stories EBF from the proposed correlation and the mean inelastic time history analysis, confirms the accuracy of the estimate relationship