## 5 Case Study and Discussion
Consequently, the plots in Figures 17d and 18d combine the probabilities of possible magnitude and distance distribution with suitable attenuation equation (here we used the Cornell, Banor and Shakal [22] as GMPE model) and with activity rate of the earthquake which followed here truncated Gutenberg-Richter relationship by hazard curves for RS1 and RS2, respectively. Notably, the source-to-site distance is affecting the exceedance rate, in which RS2 shows the maximum annual rate of exceedance is almost \(10^{-1}\) with a minimum value of \(10^{-7}\) and RS1 delivered approximately \(10^{-2}\) with a minimum value of \(10^{-14}\). These results present that the received seismic region is mostly affected by RS2. This tool calculates the hazard curve for a single source as well as the total hazard curve of all sources. However, as the source type was an area; therefore, Figure 19a reports the total hazard curves along with the single source hazard curve. As previously discussed, that the seismically most affected source is RS2, therefore in Figure 19a, the total hazard curve overlapped on the hazard curve of RS2 (calculated total hazard curve is almost equal to the RS2). Consequently, the deaggregation plot is emphasized here for source RS2 in Figure 19c. The horizontal dotted line in the annual rate of  
Figure 18: (a) Segmental view of area source, (b) Probability density function of distance, (c) Illustration of probability density function for magnitude for a source with a truncated Gutenberg–Richter distribution, (d) Probabilistic seismic hazard curve, respectively for RS2. exceedance equal to 0.00211 for 475 return period (T\({}_{R}\)) shows the peak ground acceleration (PGA) of 0.076g as shown in Figure 19b. From the deaggregation plot of the seismic site, it can be found that the nearer source-to-site of an earthquake zone will contribute more to the hazard than the remote source, but the magnitude affects the contribution in a different manner as the magnitude distribution follows recurrence law. As a result, Figure 19c shows here approximately the range of magnitude is 4 to 5 for contributing to hazard. Even though the case study has been carried out for the Cornell, Banon and Shakal [22] attenuation equation in hazard distribution, the other specific choices of GMPE models are available in PSHRisk-tool. For discussing the result of the FR-Assessment of the required case study, the fragility parameters are determined (for the considered Gunnam concrete gravity dam in South Korea) at first from the existing software ABAQUS. The fragility parameters for different damage stages such as tensile crack at the neck (LS1), relative displacement at the top of the dam (LS2) and tensile crack at the base (LS3) are1.29, 0.854 and 0.771 for a mean (\(\mu\)) value and 0.308, 0.255 and 0.244 for a standard deviation (\(\sigma\)), respectively. These values are observed and taken as the input value for FR-Assessment. As shown in Figure 19b, the total hazard curve is then combined with the failure probability expressed in Figure 20a for different damage stages. The largest risk contributions in each limit state happen in 0.80 g, 0.70 g and 0.62 g for LS1, LS2, and LS3, respectively. If it is figured out in the fragility curve for corresponding peak value in the failure risk assessment, it will focus on the probability of failure around 7.5%, 23% and 22% for LS1, LS2, and LS3, respectively. For LS1 the area under the FR-assessment curve between 0 and  
Figure 19: (a) Seismic hazard curve for all sources along with total hazard curve, (b) Total hazard curve showing the annual rate of exceedance to the corresponding 475 returned period (T\({}_{R}\)), (c) Deaggregation of PGA with 475 years T\({}_{R}\) for RS2. 0.90 g is 70%, which is dominated by the lower portion of the fragility curve for the corresponding higher-intensity. Similarly, the covered area for LS2 and LS3 can be determined and these are 80% and 80%, respectively.