عنوان مقاله [English]
Fragility curves are utilized to evaluate the probability of exceeding the damage index for structures exposed to seismic hazards. The Monte Carlo simulation method, which involves generating random numbers, is computationally expensive for calculating fragility curves. To address this issue, several methods have been proposed to produce fragility curves at a reduced computational cost. This study presents a method that enhances the seismic representation of high-dimensional models to generate accurate fragility curves for steel structures while significantly decreasing computational costs. This method selects uncertain variable values based on the results of initial incremental dynamic analyses. The fragility curves are divided into three zones, and an equation is proposed to estimate mean damage values associated with the boundaries of these zones. Additionally, polynomial response functions were generated to estimate the fragility curves. The proposed method is applied to generate the fragility curves for three steel structures, one with 4, 9, and 12 stories. Fragility curves are generated for four damage levels: non-structural damage (DS1), structural retrofitting required (DS2), intensive structural damage (DS3), and collapse (DS4). The resulting fragility curves are compared with those generated by the Monte Carlo simulation method and other existing methods. The comparison demonstrates that the proposed method achieves fragility curves with a significant decrease in computational costs compared to the Monte Carlo method, while also exhibiting higher accuracy than other methods. The maximum error of the proposed method is approximately 20%, whereas Cornell's and the conventional HDMR methods exhibit errors of up to 80% and 60%, respectively. The errors of other methods increase significantly for fragility curves associated with high damage levels and 9 and 12 story steel structures, where nonlinear structural behavior is pronounced. In contrast, the increase in error is not significant in the proposed method. The findings of this study can be utilized to assess the seismic impact of various stochastic factors, such as random eccentricity or loading-related parameters, on the vulnerability of steel structures.