## 4 Conclusions  
This study proposed a model to evaluate functionality loss during earthquakes that uses existing seismic fragility curves and statistical recovery time data for railway network components, including bridges, embankments, and tunnels. The proposed model was applied to a hypothetical railway network system to estimate the functionality loss in actual railway infrastructure during extreme earthquake scenarios. 1. Functionality loss evaluation models were derived for railway network components, including bridges, tunnels, and embankment sections. To develop functionality loss evaluation models for railway network components, seismic fragility curves for each component were analyzed, and restoration curves were derived using statistical recovery time data. Procedures for deriving functionality curves and functionality loss curves by combining seismic fragility curves and restoration curves were outlined. 2. The developed evaluation model for functionality loss of railway network components during earthquakes was applied to the Comprehensive Railway Test Line in Korea, and its applicability was assessed. To assume extreme earthquake scenarios, seismic scenarios with a seismic acceleration of 0.3 g, which exceeds the maximum 0.286 g specified in the seismic design standards of Korea, and an extreme scenario with 0.5 g were used. The distance of components was set within 32 km from the epicenter, and the depth was assumed to be shallow (10 km), similar to the Pohang earthquake. 3. For a 0.3 g earthquake, the estimated functionality loss for railway network components was 1.8-6.7% for bridge sections, 2.4-17.2% for embankments on soft ground, 0.2-1.3% for embankments on stiff ground, and 1.0-4.6% for tunnel sections. Two methods can be used to evaluate the functionality loss of the entire railway network: (1) using the maximum value or (2) calculating the average functionality loss of all network components. Using the first method, the functionality loss values for Lines 1, 2, and 3 were 12.58%, 17.21%, and 6.69%, respectively. Particularly, embankment section C had the greatest impact on the overall network, with its functionality loss of 12.58% being considered the representative functionality loss value. Using the second method, the average functionality loss ratio for the network was 3.99%. 4. For the extreme 0.5 g earthquake scenario, the representative functionality loss value was 20.1% using the same method, and the average functionality loss ratio was 9.57%. The series of analysis indicates that the functionality loss of a specific section can lead to disruptions in the overall logistics functionality of the railway network. Further studies should analyze the impact of the functionality loss of specific components on the entire network and conduct research to evaluate functionality loss at the network level. Based on this study, the functionality loss of railway network components during earthquakes, as well as the overall functionality loss of the railway network, can be quantitatively evaluated. This serves as a critical indicator for quantitatively assessing the socioeconomic impact such as disruptions in logistics caused by earthquakes. 5. This study focuses on proposing a methodology for evaluating the functionality loss of railway networks under various earthquake magnitudes. However, the case study applied in this research has two limitations. First, the scope of the railway network was not extensive, resulting in similar peak ground accelerations affecting most structures, and identical seismic fragility functions were applied uniformly within each component classification, leading to nearly identical functionality loss values for bridges, embankments, and tunnels. Second, the spatial correlation of seismic wave propagation and structural damage was not sufficiently considered, resulting in a lack of in-depth analysis of the socioeconomic impacts. 6.