Abstract
Event tree analysis (ETA) method is a straightforward and simple approach for risk assessment. It can be used to identify various sequences and their causes, and also to give the analyst the clear picture about which top event dominates the safety of the system. The traditional ETA uses a single probability to represent each top event. However, it is unreasonable to evaluate the occurrence of an event by using a crisp value without considering the inherent uncertainty and imprecision a state has. Since fuzzy set theory provides a framework for dealing with this kind of phenomena, this tool is used in this study. The main purpose of this study is to make an effort in constructing an easy methodology to evaluate the human error and integrates it into ETA by using fuzzy concept. In addition, a systematic FETA algorithm is developed to evaluate the risk of a large scale system. A practical example of an ATWS event in a nuclear power plant is used to demonstrate the procedure. The fuzzy outcomes will be defuzzified by using the total integral value in terms of the degree of optimism the decision maker has. At last, more information about the importance and uncertainty of top events will be provided by using the two indices.