Pin power reconstruction for CANDU reactors using a neuro-fuzzy inference system

A neuro-fuzzy inference system has been developed for reconstructing fuel pin powers from Canada deuterium uranium (CANDU) core calculations performed with a coarse-mesh finite difference diffusion approximation and single-assembly lattice calculations. The neuro-fuzzy inference system is trained by a genetic algorithm and a least-squares method using the partial core calculation results of two 6×6 fuel bundle models. Verification tests have been performed for two partial core benchmark problems composed of other 6×6 and 3×3 fuel bundles. The reconstructed pin powers are compared with the reference solutions obtained with the detailed collision probability calculations using the HELIOS lattice analysis code. The results indicate that the proposed reconstruction algorithm is accurate, yielding the error due to the reconstruction scheme of less than 0.5%