## 1 Introduction
examined various aspects related to the computation of the mean annual frequency of collapse and showed that the mean annual frequency of collapse is dominated by earthquake ground motion intensities. Also, it was shown that uncertainty in the collapse fragility curve and mean annual frequency of collapse can be expressed as a function of the number of ground motions used in calculations [16]. [PERSON] et al. presented on the seismic fragility of 15 RC school buildings built between 1960 and 1980s in Southern Italy. In their study, a practical mode for application of the multi-stripe analyses was proposed and SPO2 FRAG v1.1(beta) software was used to predict the median and the record-to-record variability of the seismic response of an SDOF system, and to provide the fragility curves for each limit state [17]. [PERSON] et al. proposed a framework for efficient risk assessment of multi-span girder bridges considering knowledge-based uncertainties. From a case study, it addressed issues such as the use of optimal intensity measures, the required number of model realizations and discrepancies with respect to accurate nonlinear time history analysis [18]. [PERSON] et al. proposed an alternative time-dependent seismic fragility assessment framework for aging highway bridges. In the study, they pointed out that the variation in the peak value of seismic response may result from the couple contributions of the uncertainty of ground motions and modeling related parameters [19]. [PERSON] and [PERSON] studied epistemic uncertainty in the relationship between material constitutive models and seismic fragility curves for reinforced concrete structures, analyzing two design options for the girders and columns of steel structures by considering various material model variables. Seismic fragility curves were derived for three performance levels using IDA with 30 ground motions [20]. [PERSON] et al. conducted a study on epistemic uncertainty regarding IMs, damage classification criteria, target facility selection methods, and seismic fragility generation methods for damage caused by tornadoes in the Joplin, Missouri, area [21]. Recent advancements in technology, including increased computing power, have made it possible to perform numerical analyses on large and complex structures that used to be difficult to handle, allowing for seismic fragility analysis with many ground motions. The appropriate number of ground motions must first be determined when using methods such as IDA, which is widely used for generating seismic fragility curves. Afterward, different magnitudes of ground motions are selected, and numerical analysis is performed on combinations of the number and magnitude of ground motions, considering damage levels to generate the fragility curves [22; 23]. Seismic fragility refers to the probabilistic vulnerability of a structure to ground motion variability. If the number of ground motions is insufficient, the diversity of the ground motions is inadequately considered, distorting the fragility results. Conversely, considering numerous ground motions increases the diversity of the ground motions and improves the accuracy of the fragility curves; however, it requires an excessively long analysis time. Therefore, when generating seismic fragility curves, the number of ground motions used is directly linked to the numerical analysis time, making it crucial to consider an appropriate number and magnitude of ground motions. Ground motions used in seismic fragility curves are key input variables in seismic vulnerability analysis and inherently involve uncertainty in the numerical model of the target facility and the selection of input ground motions. Epistemic uncertainty, arising from limitations in knowledge and data, can significantly impact the reliability of seismic fragility curves. This study derived seismic fragility curves by considering many ground motions and analyzed the relationship between the key input variables of the fragility curves and the number of ground motions used in generating the fragility curves.