Quantitative Risk Assessment (QRA) is a classical method for the calculation of risk in process plants, which is based on the logic of the consequence analysis. This intrinsically probabilistic method has been thought for classical accident conditions, where the damage events and the relevant consequences start from a preselected component and a standard loss of containment (LOC) and follow all possible scenarios for the calculation of individual and societal risk. This final risk metric is usually expressed in terms of probability of fatality in a specific location of the surrounding area or a certain number of fatalities in the area surrounding the accident. In presence of Na-Tech events, like earthquakes, a multi-source condition can be caused by multi-damage conditions simultaneously involving more than one equipment, which in turn can generate a multiple-chain of events and consequences. In literature, several attempts of modifying the classic QRA approach to account for this important aspect have been formalized without converging toward a unified approach.
In this paper, a fragility-based method for Quantitative Seismic Risk Analysis (QSRA) of a process plant is investigated. This method takes into account all possible damage/losses of containment conditions in the most critical equipment, e.g., storage tanks. Fragility curves, which are analytically evaluated for each unit with respect to its seismic damage conditions, are utilized inside the procedure. The Monte Carlo Simulation (MCS) method is then used with the aim to follow all steps of QSRA. In particular, starting from the seismic hazard curve of the site where the plant is placed, a multi-level approach is proposed. In this approach, the first level is represented by the components seismically damaged, whereas the following levels are treated through a classical consequence analysis, including the propagation of multiple simultaneous and interacting chains of accidents. These latter are applied by defining proper correspondences for all relevant equipment between structural damage (i.e., limit states) and LOC events. The application of the method to an actual process plant permits to investigate its high potentiality and the dependency of the risk assessment from the proper fragility models.