Hot spot identification by sensitivity analysis and probabilistic inference methods: Demonstration exercise

The method for identifying the presence of hot spots in the core of a nuclear reactor described in a previous note (Gandini, 2011) is applied in a demonstration exercise relevant to a simplified, medium size PWR reactor. By this method the information obtained on-line through a system of neutron measuring devices such as self-powered neutron detectors (SPNDs, or collectrons) inserted in the core of a nuclear power reactor allows the on-line quick detection of a possible hot spot during plant operation. The method is based on the generalized perturbation method (GPT) techniques for the calculation of the sensitivity coefficients of the integral quantities measured with the collectrons with respect to parameters representative of the hot spot, and on the use of probabilistic inference techniques, taking into account the errors associated with the measurements. The methodology allows to assess the effect on the quality of the hot spot detection system following possible failures of the measuring devices during the core life cycle. Such an assessment may be useful for defining an adequate protection strategy in terms of quality, number and distribution of the collectrons. The results obtained with the exercise demonstrate the validity of the proposed method.

► A method is adopted exploiting SPND detector information for hot spot identification. ► The method uses sensitivity coefficients by GPT method to obtain hot point estimates. ► The effect of a detection device system degradation may be taken into account. ► A demonstration exercise validates the methodology.