## 3 Results and Discussion
### Simulation of Seismic Response and Reliability  
After the optimal modeling parameters are determined and the FEM with limited information is updated, the resultant model can be used as a baseline to predict structural performance under hazardous events. Specifically, in this study, seismic response is scoped, yet similar analysis procedure can be extended to other damaging events. The PEER Strong Motion Database have an extensive set of real earthquake records, therefore, one of these largest sets, 1994 Northridge Earthquake is taken as an exemplary structural demand due to a seismic event [59]. Table 2 shows the overall information about the ground motion dataset features and strong motion parameters. One hundred and fifty-one earthquake ground motion records are taken from the Northridge Earthquake dataset and used as structural input for time history analyses. With the time history analysis of the baseline model under different earthquake ground motions, the structural response can  
Figure 9: Updated FEM modal parameters for fixed-fixed, fixed-pinned, fixed-roller BCs. be probabilistically simulated. Figure 10 shows an example of these analyses illustrating the time and the frequency content of the structural input and outputs. According to Figure 10, it can be observed that the frequency content of the input ground motion is dominated in low frequencies (below 5 Hz), whereas the structural response peaks around 8-9 Hz. The mode with the lowest frequency, the first mode, is excited more than the second and third modes, and therefore, the response peaks are observed around the first frequency range. This is due to the fact that the higher structural frequencies (e.g., 8.5, 19, 29 Hz) are very far away from relatively low frequency seismic activity. For these reasons, the seismic response is expected to have less structural damage compared with the low frequency civil infrastructure. As a result, the structure behaves in the linear range, yet, it should still be checked whether the bridge maximum deformations exceed certain regulations. One reason is, the nonstructural earthquake damage losses still compose a significant percentage of overall losses [60]. Likewise, even slight damages following a seismic event might result in functionality losses [61]. Besides, it is seen that the low-frequency sensitive displacement response still includes the effects of seismic input, whereas these effects vanish in case of the acceleration response. Finally, and the most important of all, excessive displacements occurring at facade components can lead to glass failure, which possesses safety threat for campus occupants nearby the bridge during the catastrophic incident [62; 63]. To summarize the overall dataset results, Figure 11 shows the maximum acceleration and displacement response values indexed according to the strong motion parameters amplitude, frequency, and duration [64], respectively. The analysis results are obtained considering the excitation in the vertical direction. Location of the output corresponds to the absolute maximum displacement value observed on multiple bridge deck nodes throughout the time history analyses. Time history analysis results are recorded and the maximum response values from each analysis are collected to form a distribution demand. Figure 12 shows the distributed and the cumulative maximum displacement distribution obtained from 151 analysis results. Assuming that the distribution \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ground Motion Parameter** & **Range 1** & **Range 2** & **Range 3** & **Range 4** \\ \hline Frequency (Hz) & 0–3 & 3–6 & 6–10 & 10–50 \\ Number & 112 & 37 & 2 & 0 \\ PGA (g) & 0–0.1 & 0.1–0.4 & 0.4–1 & 1–2 \\ Number & 50 & 70 & 29 & 2 \\ Duration (s) & 0–25 & 25–50 & 50–75 & 75–100 \\ Number & 17 & 120 & 14 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Ground motion dataset summary. Figure 10: Exemplary input ground motion and simulated structural response.