Diagnostics of VVER-1000 core states by reactivity perturbations

The self-sustained nuclear fission chain reaction is based on the probabilistic nature of fundamental physical processes. The measure of the dynamics of these processes (state identifier) is taken to be reactivity as a special physical property of the medium or technical system. The paper proposes to attribute reactivity to the class of random functions with zero mathematical expectation in the stationary critical state. Fluctuations with respect to zero value are perceived as a result of external factors causing an instantaneous response of the core of reactor plants operating at the installed power for the main part of the operating time. This definition is sufficient to develop methods of technical diagnostics based on perturbations of the reactivity of the core. The reactor core is considered as a stochastic object that is kept within the normative field of its design and regime characteristics. According to the archive data of reactivity ‘measurements’, it is possible to correlate to certain states of the reactor core the fragments of stochastic time series, which would serve as identifiers of these states. The set of such fragments (tests) constitutes a library of NPP operation experience. In the present work, the effects of an external Poisson perturbation of reactivity and the classification of neutron density modulations arising therefrom are considered in the framework of the one-group kinetics model. The reflection in the probabilistic characteristics of neutron density of random static and dynamic regime factors through reactivity is perceived as evidence of generation of defectiveness of the reactor core. The deterministic component of neutron density is described quite accurately by the equations of kinetics and corresponds to the trend of the mathematical expectation of reactivity with respect to zero value. A procedure of processing the data of neutron flux control equipment and reactor intrinsic control system is proposed, which includes formation of a library of test perturbations on the basis of archived data; analysis of responses by the Kolmogorov-Smirnov criterion of agreement between the empirical distribution functions of the current sample of empirical data and those calculated by the equations of kinetics on the basis of the library of perturbations. It is argued that the proposed procedure is a means of identifying the defect level of the core and can also be used as an event simulator in deep learning of a classifying neural network. The results refer to the achievements of neutron-noise diagnostics.