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Consultant recommends subsidies for Exelon plants
A research and consulting firm hired by Illinois governor J. B. Pritzker’s administration to scrutinize the financial fitness of Exelon’s Byron and Dresden nuclear plants approves of limited state subsidies for the facilities, according to a redacted version of the firm’s report made available yesterday.
A. Hoefer, G. Dirksen, J. Eyink, E.-M. Pauli
Nuclear Science and Engineering | Volume 166 | Number 3 | November 2010 | Pages 202-217
Technical Paper | dx.doi.org/10.13182/NSE10-09
Articles are hosted by Taylor and Francis Online.
In a level-2 probabilistic safety analysis (PSA), two types of uncertainty have to be taken into account: the uncertainty related to random variation (variability) and the uncertainty related to limited knowledge (ignorance). We present a consistent treatment of these two types of uncertainty within a Bayesian framework. This framework allows us to translate both types of uncertainty in the basic parameters into branch probability distributions of the PSA accident progression event tree (APET). This, in turn, results in probability distributions for the different release categories. A generic Monte Carlo algorithm for drawing random samples from branch probability distributions is presented, offering the possibility to directly include information in terms of empirical data. To provide an illustrative example, the developed methods are applied to a specific APET question, related to the temperature-induced rupture of the reactor coolant system in case of a high pressure accident scenario. Although this paper addresses level-2 PSA, the proposed framework is presented in a general form to be applicable to other PSA problems.