AN OVERVIEW OF THE PRINCIPLES OF MODELING CHARPY IMPACT ENERGY DATA USING STATISTICAL-ANALYSES

Integrity assessments of Magnox nuclear reactors with steel pressure v essels quantify the temperature margins between the operating temperat ure of the plant, at any given location, and the onset of upper-shelf temperature. The onset of upper-shelf temperature can be estimated fro m the fracture toughness properties of each material used in the const ruction of the pressure vessels. Although start-of-life fracture tough ness properties of the materials have been measured, such properties a re not available for the neutron-irradiated and thermally aged conditi on. One of the main effects of neutron irradiation and temperature exp erienced during service is to increase the ductile-to-brittle transiti on temperature (DBTT), which can be represented in terms of temperatur e shifts. In the irradiation surveillance schemes for the Magnox react ors, these temperature shifts can be inferred from Charpy impact energ y data which have been measured regularly during the service life. Sin ce Charpy impact energy data are inherently scattered, it is necessary to optimize the interpretation of the data by statistical processing. A recent analysis undertaken by Moskovic et al. concluded that Bayesi an analyses are best suited to address the problem. In this overview, we consider the requirements of such analyses and the various options available. We then consider the method proposed by Moskovic et al. wit h respect to the requirements of the inputs to the integrity assessmen t and the validity of this approach. In this method of analysis, the d istribution of all possible values of model coefficients is establishe d by judging the various possible combinations of these model coeffici ents in relation to the likelihood of the observed data. Analysis of a rtificially generated data has been used to compare the effectiveness of Bayesian analyses with those used traditionally.