Dynamic fault trees resolution: A conscious trade-off between analytical and simulative approaches

Abstract

Safety assessment in industrial plants with ‘major hazards’ requires a rigorous combination of both qualitative and quantitative techniques of RAMS. Quantitative assessment can be executed by static or dynamic tools of dependability but, while the former are not sufficient to model exhaustively time-dependent activities, the latter are still too complex to be used with success by the operators of the industrial field. In this paper we present a review of the procedures that can be used to solve quite general dynamic fault trees (DFT) that present a combination of the following characteristics: time dependencies, repeated events and generalized probability failure. Theoretical foundations of the DFT theory are discussed and the limits of the most known DFT tools are presented. Introducing the concept of weak and strong hierarchy, the well-known modular approach is adapted to study a more generic class of DFT. In order to quantify the approximations introduced, an ad-hoc simulative environment is used as benchmark. In the end, a DFT of an accidental scenario is analyzed with both analytical and simulative approaches. Final results are in good agreement and prove how it is possible to implement a suitable Monte Carlo simulation with the features of a spreadsheet environment, able to overcome the limits of the analytical tools, thus encouraging further researches along this direction.