Neutron noise source reconstruction using the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the VVER-1000 reactor core

Abstract

The neutron noise is defined as the stationary fluctuation of the neutron flux around its mean value due to the induced perturbation in the reactor core. The neutron noise analysis may be useful in many applications like noise source reconstruction. To identify the noise source, calculated neutron noise distribution of the detectors is used as input data by the considered unfolding algorithm. The neutron noise distribution of the VVER-1000 reactor core is calculated using the developed computational code based on Galerkin Finite Element Method (GFEM). The noise source of type absorber of variable strength is considered in the calculation. The computational code developed based on An Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to unfold the neutron noise source. Complex neutron noise distribution (real and imaginary parts) in the detectors is considered as input data onto the developed computational code based on the ANFIS algorithm. All the characteristics of the neutron noise source, including strength, frequency and position (X and Y coordinates) are unfolded with excellent accuracy using the developed computational code.