APPLICATION OF PYTHON PROGRAMMING TOOLS FOR CRITICALITY SIMULATION OF NEUTRON TRANSPORT IN NUCLEAR REACTOR WITH SLAB GEOMETRY

Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue () and eigenfunction (fission source distribution) of the fundamental mode. However, the main problems of this method are the slow convergence of fission source distribution from the initial guess to the stationary solution, and the correlation between successive cycles which results in an under-prediction bias in the confident intervals of the estimated response. In this paper, we presented the Wielandt's method aiming to accelerate the convergence of the Monte Carlo power iteration.The object-oriented programming called Python prototype, was used to describe the standard Monte Carlo criticality power iterations for mono-kinetic particles and to compare the results obtained by the two different methods of acceleration mentioned above. The Wielandt's method successfully suppressed the auto-correlation, even though no gain in the figure of merit seemed to occur.