Conventional and dynamic safety analysis: Comparison on a chemical batch reactor

Abstract

Dynamic safety analysis methodologies are an attractive approach to tackle systems with complex dynamics (i.e. with behavior highly dependent on the values of the process parameters): this is often the case in various areas of the chemical industry. The present paper compares analyses with Probabilistic Safety Assessment (PSA)/Quantitative Risk Assessment (QRA) methods with those from a dynamic methodology (Monte Carlo simulation). The results of a case study for a chemical batch reactor from the literature, overall risk figure and main contributors, are examined. The comparison has shown that, provided that the event success criteria are appropriately defined, consistent results can be obtained; otherwise important accident scenarios, identifiable by the dynamic Monte Carlo simulation, are possibly missed in the application of conventional methods. Defining such criteria was quite resource-intensive: for the analysis of this small system, the success criteria definitions required many system simulation runs (about 1000). Such large numbers of runs may not be practical in industrial-scale applications. It is shown that success criteria obtained with fewer simulation runs could have led to different quantitative PSA results and to the omission of important accident scenario variants.