Methodology for tunnel risk assessment using fault and event tree analysis

Zlatko Zafirovski, Vasko Gacevski, Zoran Krakutovski, Slobodan Ognjenovic, Ivona Nedevska

Last modified: 2023-06-02

Abstract


The intense demand and construction of tunnels is accompanied by uncertainties. The reason for appearance of uncertainties are the complex solutions and conditions for these structures. Location and dimensions are becoming more challenging, and the construction is predicted in complexed geological conditions, leading to application of new approaches, methodologies and technologies by the engineers. Most of the uncertainties and unwanted events in tunnelling occur in the construction phase, which generally leads to economic consequences and time losses. For easier handling of the uncertainties, they should be anticipated and studied within a separate part of each project. One of the newer approaches to dealing with uncertainties is hazard and risk assessment and defining ways to deal with them i.e. management. Hazards and risks can be analyzed qualitatively and quantitatively. The quantitative analysis, examines the causes and consequences in more detail way and gives explanation of the dependencies. With the quantitative approach, a more valuable information for decision-making can be provided. There are various models and methods used for the quantification of hazards and risks. This paper presents a methodology in which the fault tree analysis and event tree analysis are used in combination to obtain quantitative results. The fault tree analysis is used for assessment of various hazards and the different ways and reasons that cause them. The event tree analysis is a method for assessing the possible scenarios, which follow after a certain hazard i.e. the consequences that may occur in the project. These trees represent graphic models combined with a mathematical (probabilistic) model, which give the probability of occurrence of the risks.

Keywords


tunnels; uncertainties; risks; fault tree analysis; event tree analysis;

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