عنوان مقاله [English]
Nonlinear Time History Analysis (NTHA) contains a complex and rigorous process for structural seismic evaluation. Nonlinear static analysis (pushover) can simplify this process. However, pushover analysis has some shortcomings. In pushover-based procedures, displacement is known as the main indicator of structural capacity. Whereas, structural responses include force and displacement components. Therefore, energy is able to address these shortcomings by considering force and displacement, simultaneously. This paper aims to develop an energy-based seismic assessment methodology, using pushover analysis. This methodology can estimate the response of mid-rise buildings with much fewer computational operations than nonlinear time history analysis and consider higher mode effects. Other advantages of the proposed methodology include using the capacity curve of multiple degrees of freedom (MDOF) systems directly instead of the equivalent single degree of freedom (ESDOF) and computing the energy demand of the structure based on the mean spectrum corresponding to the desired hazard level instead of the various earthquake record spectrums. In the proposed methodology, the pushover capacity curve is converted to the energy capacity curve for each mode and the energy demand curve is superimposed on it. The intersection of these two curves is considered as the target response. In order to validate and compare the results of the proposed methodology with other procedures, in addition to the proposed methodology, NTHA and Modal Pushover Analysis (MPA) are employed. Also, 8 and 9-story steel moment frame buildings are selected, modeled, and analyzed using OpenSEES software. The results show that the proposed methodology is able to estimate the responses of the building with reasonable accuracy compared to the mean results of the NTHA. Also, the proposed methodology significantly reduces the error of the responses compared to the MPA. Nevertheless, it can be concluded that the proposed energy-based methodology is a simple, efficient, and rapid alternative for nonlinear time history analysis.