Abstract
An uncertainty analysis is required to be carried out in formal safety assessment (FSA) by the International Maritime Organization. The purpose of this article is to introduce the uncertainty analysis technique into the FSA process. Based on the uncertainty identification of input parameters, probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. An approach which combines the Monte Carlo random sampling of probability distribution functions with the a-cuts for fuzzy calculus is proposed to propagate the uncertainties. One output of the FSA process is societal risk (SR), which can be evaluated in the two-dimensional frequency–fatality (FN) diagram. Thus, the confidence-level-based SR is presented to represent the uncertainty of SR in two dimensions. In addition, a method for time window selection is proposed to estimate the magnitude of uncertainties, which is an important aspect of modeling uncertainties. Finally, a case study is carried out on an FSA study on cruise ships. The results show that the uncertainty analysis of SR generates a two-dimensional area for a certain degree of confidence in the FN diagram rather than a single FN curve, which provides more information to authorities to produce effective risk control measures.
Highlights
Formal safety assessment (FSA), aimed at enhancing maritime safety, is a structured and systematic methodology
The purpose of the risk analysis in step 2 is a detailed investigation of the causes and initiating events and consequences of the more important accident scenarios identified in step 1
The scope of the FSA, types of hazards identified in step 1, and the level of data available will all influence which method works best for each specific application
Summary
Formal safety assessment (FSA), aimed at enhancing maritime safety, is a structured and systematic methodology. FSA comprises five steps: identification of hazards (step 1), risk analysis (step 2), risk control options (step 3), cost–benefit assessment (step 4) and recommendations for decision-making (step 5). The output from step 2 can be used to identify the high-risk areas so that the effort can be focused to produce effective risk control measures in step 3 of the FSA [1]. There are several methods that can be used to perform a risk analysis, and different types of risk (i.e. risks to people, the environment or property) can be addressed according to the scope of the FSA. The scope of the FSA, types of hazards identified in step 1, and the level of data available will all influence which method works best for each specific application
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