Risk assessment of railroad for the presence of underground cavities based on a statistical approach

Abstract

Collapses due to underground cavities have been drastically increasing in urban areas of South Korea. This article establishes a statistical model to assess the risk potential of railroads with respect to underground cavities. The authors first identified the risk factors of the event based on case studies where the collapses of underground cavities took place. The database was then established, taking into account the risk factors, to come up with a statistical model that estimates the risk level. In this study, the maximum likelihood estimation (MLE) method was employed to estimate the parameters in a statistical model. Thorough the statistical analysis, the probability of underground cavity occurrences was found to be expressed in terms of the depth of alluvial layer, groundwater level, water and sewage utilities, and their age. Consequently, an attempt was made to generate a preliminary hazard map for a specific railway route by employing the statistical model.