• Journal of the Korea institute for structural maintenance and inspection
• /
• v.22 no.5
• /
• pp.110-118
• /
• 2018

Due to recent earthquakes, there is a growing awareness that Korea is not a safe zone for earthquakes any more. Therefore, the review of various aspects of the seismic safety of the infrastructures are being carried out. Because of the characteristics of the underground structure buried in the ground, the electric power utility tunnels must be considered not only for the inertia and load capacity of the structure itself but also the characteristics of the surrounding soils. An extensive and accurate numerical analysis is inevitably required in order to consider the interaction with the ground, but it is difficult to apply the soil-structure interaction analyses, which generally requires high cost and extensive time, to all electric power utility tunnel structures. In this study, the major design variables including soil characteristics are considered as independent variables, and the seismic safety factor, which is the result of the numerical analysis, is considered as a dependent variable. Thus, a method is proposed to select vulnerable electric power utility tunnels with low seismic safety factor while excluding costly and time-consuming numerical analyses through the direct correlation analysis between independent and dependent variables. Equations of boundary limits were derived based on the distribution of the seismic safety factor and the cover depth and rebar amounts with high correlation relationship. Consequently, a very efficient and simple approach is proposed to select vulnerable electric power utility tunnels without intensive numerical analyses. Among the 108 electric power utility tunnels that were investigated in this paper, 30% were screened as fragile structures, and it is confirmed that the screening method is valid by checking the safety factors of the fragile structure. The approach is relatively very simple to use and easy to expand, and can be conveniently applied to additional data to be obtained in the future.