Examining the Impact of Adverse Weather on Urban Rail Transit Facilities on the Basis of Fault Tree Analysis and Fuzzy Synthetic Evaluation

Abstract

The increasingly frequent extreme weather disasters caused by global climate change have attracted more attention to adverse weather’s effect on infrastructure systems. This paper aims to establish an integrated approach to assessing adverse weather’s effect on urban rail transit facilities and to provide decision makers with a powerful tool to analyze potential risks and allocate limited sources for risk management. First, fault tree analysis is used to understand where the risks are, how the risks will occur, and what factors have the most significant effects by analyzing all possible basic events. All wind-, rain-, and snow-related adverse weather, along with human-related factors (construction leftover problems and design drawbacks), are found to potentially cause great risks. Adverse impact scenarios are summarized based on the fault tree analysis. Next, an analytic hierarchical process (AHP)–based fuzzy synthetic evaluation model is established to assess the risk level based on an evaluation index system. AHP is used to calculate the weights between the indices for each adverse weather factor. A fuzzy synthetic evaluation process is then carried out to identify the risk level of an evaluation target, an urban rail transit station, or line section. A case study on the Beijing URT Line 8 Olympic Center Station is conducted to illustrate the process of evaluation. The results show that the risk level is high and it becomes acceptable only after countermeasures are taken. Potential countermeasures regarding facility capacity, protection area management, and monitoring/inspection are then briefly discussed.