Evaluation of the Updated Site-Specific Risk Assessment for the National Bio- and Agro-Defense Facility in Manhattan, Kansas (2012) / Chapter Skim
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3 Evaluation of Risk Approach and Calculations
3 Evaluation of Risk Approach and Calculations
Pages 23-36
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From page 23... ...
The framework includes the identification of risk scenarios, calculation of event likelihoods as annual frequencies of occurrence, assessment of consequences of an infection event, calculation of annual expected consequences, total calculation of risk of all events, and uncertainty analysis. APPLICATION OF RISK METHODS IN THE UPDATED SITE-SPECIFIC RISK ASSESSMENT The modeling framework is a "scenario-based" approach that is well established for analyzing risk in complex systems.
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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)
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. Values for human error rates in work settings similar to the NBAF should be based on related empirical evidence.
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The uSSRA claims that NBAF workers would be more highly skilled than "skilled workers" and provides an error rate of 5 × 10–3 of failure per error opportunity with no further substantive explanation. It was critical for the uSSRA to have explored possible sources of data and operating experience related to human errors in research laboratory settings as the basis of generic or reference error probability.
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Failure to include this type of human error, referred to as slip error, would in essence mean that the model assumes the slip error rate to be zero. Sensitivity and Uncertainty Analysis A critical part of risk analysis is characterizing the uncertainty in the results and the sensitivity of those results to changes in assumptions or parameter values.
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From page 28... ...
Both are meaningful only in the context of a probability distribution, and the distributional assumptions for the input parameters are unclear. A major concern regarding the treatment of uncertainty is exemplified in how the point estimate and uncertainty distributions are calculated for Pi (the conditional probability of infection)
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As previously stated, the correct quantity that is used in uncertainty quantification is the actual variable Pi and not its mean value Pi . • One implication of assumptions behind the calculation of the (mean)
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Treatment of Dependencies It is of fundamental importance in probabilistic modeling to correctly characterize probabilistic dependencies among events and model variables and to account for such dependencies in calculating probabilities of the joint occurrence of those events and parameters. The committee finds that the uSSRA ignored potential dependencies in calculating probabilities for the risk scenarios and that this likely resulted in a serious underestimation of the total risk and in incorrect ranking of risk contributors.
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From page 31... ...
For one parallel caisson to exhaust unfiltered room air, there would have to be two filter failures, two primary alarm failures, and a redundant alarm failure. Therefore the uSSRA states that the probability of this event is given by Pevent = (PFAIL*
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The event tree design omitted critical events that could lead to an FMD event by ignoring risk of out-ofcontainment leaks. These were identified by the previous National Research Council committee as a shortcoming (NRC, 2010)
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6. Glove failure rates and Tyvek suit reduction rates.
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Figures The quantitative information presented in some of the figures in the uSSRA was not immediately obvious to the committee, often because the figures lacked sufficient annotative details. That is exemplified by, but not limited to, Figure 5.1.9-6 (p.
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2005. Power Failure Hits CDC Germ Lab.
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2008. CDC: Offline generators caused germ lab outage.
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