## 3 Analyze Results and Discussion
Therefore, evaluating this earthquake solely based on data from either station 4615 or station 4611 would result in inaccurate data interpretation. To properly assess the province of Kahramanmaras, this study selected two stations: station 4615, which was closer to the earthquake's focal point than Kahramanmaras, and another station that was farther away. The average performance of the buildings at these two stations was used to determine the overall building performance in the region. Kahramanmaras province was approximately 40 km away from the epicenter of the earthquake. This distance can be considered an average of the two selected stations (13.83 km/\({}^{2}\) + 55.32 km/\({}^{2}\) = 34.575 km, for station 4615 and station 4611, respectively). In this way, it was believed that the destruction in the province of Kahramanmaras would be represented more realistically. The evaluated performance levels of the investigated structures are given in Table 8 and presented in Figure 17. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **IO (\%)** & **LS (\%)** & **CP (\%)** & **C(\%)** \\ \hline \multicolumn{5}{c}{**All Buildings and Both Stations**} \\ \hline Old & 6.27 & 76.56 & 7.57 & 9.60 \\ New & 7.39 & 85.80 & 4.86 & 1.96 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Percentage of each evaluated performance level of investigated structures. Figure 18 compares the probability distributions of the old and new buildings across different performance levels. The graph on the left represents older buildings, while the graph on the right represents newer buildings. For older buildings, the immediate occupancy (IO) level quickly reaches 100% probability at small \(\Delta/\mathrm{H}\) values (below 0.5%), whereas in newer buildings, this level is attained at slightly larger \(\Delta/\mathrm{H}\) values (around 0.7%). At the Life Safety (LS) level, older buildings reach a 100% probability at approximately 1% \(\Delta/\mathrm{H}\), while newer buildings can withstand deformations up to 1.5%. Similarly, at the Collapse Prevention (CP) level, older buildings quickly reach 100% probability with smaller deformations, while newer buildings reach this level at higher \(\Delta/\mathrm{H}\) values (2-2.5%). A comparable trend is observed at the collapse (C) level, as older buildings reach 100% probability at around 3% \(\Delta/\mathrm{H}\), whereas newer buildings can tolerate deformations up to 4%. Overall, newer buildings demonstrate greater durability than older buildings across all performance levels and provide enhanced safety against larger deformations. The fragility curves [26; 27; 28] presented in Figure 17 were developed using a lognormal cumulative distribution function (CDF) to estimate the probability of exceeding specific damage states, with the normalized roof drift demand (\(\Delta/\mathrm{H}\)) used as the engineering demand parameter (EDP) [29]. The fragility function is formulated based on Equation (3) and shown in Figure 17.  
\[\mathrm{P}(\mathrm{D}>\mathrm{Si}\mid\mathrm{IM})=\Phi\frac{\ln(IM)-\ln(\mu)} {\sigma} \tag{3}\]  
In this context, \(P\) represents the probability of structural damage (\(D\)) exceeding a given damage state (\(Si\)); \(\Phi\) denotes the standard normal cumulative distribution function; \(IM\) is the selected intensity measure value; \(\sigma\) is the lognormal standard deviation; and \(\mu\) is the mean of the natural logarithm of the seismic intensity measure. Based on the nonlinear time history analyses conducted, a demand-to-capacity comparison was carried out for each building evaluated within the scope of the study, and the percentage distribution of building performance levels is presented in Table 7. Following this, the results were compared with findings from field studies reported in the  
Figure 17: Cumulative exceedance curves for new and old buildings. literature on the 6 February 2023 Kahramanmaras earthquakes, and the outcomes were discussed accordingly.