ON THE USE OF EXPERT JUDGMENTS TO ESTIMATE THE PRESSURE INCREMENT IN THE SEQUOYAH CONTAINMENT AT VESSEL BREACH

The use of expert judgments in probabilistic risk assessments has become common. Simple aggregation methods have often been used with the result that expert biases and interexpert dependence are often neglected. Sophisticated theoretical models for the use of expert opinions have been proposed that offer ways of incorporating expert biases and dependence, but they have not found wide acceptance because of the difficulty and rigor of these methods. Practical guidance on the use of the versatile Bayesian expert judgment aggregation model is provided. in particular, the case study of pressure increment due to vessel breach in the Sequoyah nuclear powerplant is chosen to illustrate how phenomenological uncertainty can be addressed by using the Bayesian aggregation model. The results indicate that the Bayesian aggregation model is a suitable candidate model for aggregating expert judgments, especially if there is phenomenological uncertainty. Phenomenological uncertainty can be represented through the dependence parameter of the Bayesian model. This is because the sharing of assumptions by the experts tends to introduce dependence between the experts. The extent of commonality in the experts' beliefs can be characterized by assessing their interdependence. The results indicate that uncertainty is possibly underestimated by ignoring dependence. Two Bayesian approaches are used. The first approach uses the experts' opinions as evidence to update the decision maker's state of knowledge. The second approach, in recognition of the fact that the experts are highly dependent on a common information source, assumes that the common information source is the actual expert and the participants are assessing its biases and credibility. The results lend validity to the use of weighted averaging schemes because the Bayesian aggregation method encompasses simple arithmetic and geometric averaging techniques.