Estimating the Frequency of Nuclear Accidents. Issue 1 (2nd January 2016) - Raju, Suvrat
ABSTRACT: Bayesian methods are used to compare the predictions of probabilistic risk assessment—the theoretical tool used by the nuclear industry to predict the frequency of nuclear accidents—with empirical data. The existing record of accidents with some simplifying assumptions regarding their probability distribution is sufficient to rule out the validity of the industry's analyses at a very high confidence level. This conclusion is shown to be robust against any reasonable assumed variation of safety standards over time, and across regions. The debate on nuclear liability indicates that the industry has independently arrived at this conclusion. Paying special attention to the case of India, the article shows that the existing operating experience provides insufficient data to make any reliable claims about the safety of future reactors. Finally, policy implications of the article findings are briefly discussed.