Defining risk as an expected (probability weighted) consequence is consistent with current practice, but this metric masks the difference between high-probability/low-consequence events and low-probability/high-consequence events. That approach is not incorrect, but a preferred and more informative metric would be the probability–consequence “risk curve” in which various levels of consequence (Cevent) are plotted against corresponding probabilities (Pevent) (Cox, 2009). Although this is not a fundamental flaw in the chosen approach, presenting outcomes in the more informative way would have provided richer information to the reader.
The Logic Modeling Approach
The uSSRA uses a non-binary event tree modeling technique, which is appropriate and standard present practice. Whereas the technique seems to be correctly applied, it is difficult to understand the analysis and its results. The uSSRA uses fault tree symbols at branch points of the event trees, which is confusing and suggests a poor understanding of basic terminology. The uSSRA incorrectly refers to the event trees as fault trees in most cases but refers to them as event trees in others.
Typical risk scenarios in the report involve a temporal sequence of events; therefore, an event tree approach is effective for enumerating all possible chains of events in a scenario. In modeling failure of system components, however, a fault tree approach provides a better way of capturing system failure paths (e.g., minimal cut sets) than the event tree approach (Cox, 2009). For this reason, many industrial installations use risk analyses that are a hybrid of event trees and fault trees (Cox, 2009). The uSSRA should have followed suit by using a hybrid model, but it did not.
Mean Versus Median
The uSSRA lacks a consistent approach to calculating middle values or best estimates. Most of the risk calculations use the estimated 50th per-centile (the median); some use the mean (for example, see discussion on Q values on p. 578 of the uSSRA). The median and mean can differ by orders of magnitude in highly skewed distributions, which appear to be the case for many parameters in the risk calculations. A consistent approach should have been used in the uSSRA, and it should have relied upon the mean rather than the median.