Time series analysis and Monte Carlo methods for eigenvalue separation in neutron multiplication problems

A time series approach has been applied to the nuclear fission source distribution generated by Monte Carlo (MC) particle transport in order to calculate the non-fundamental mode eigenvalues of the system. The novel aspect is the combination of the general technical principle of projection pursuit for multivariate data with the neutron multiplication eigenvalue problem in the nuclear engineering discipline. Proof is thoroughly provided that the stationary MC process is linear to first order approximation and that it transforms into one-dimensional autoregressive processes of order one (AR(1)) via the automated choice of projection vectors. The autocorrelation coefficient of the resulting AR(1) process corresponds to the ratio of the desired mode eigenvalue to the fundamental mode eigenvalue. All modern MC codes for nuclear criticality calculate the fundamental mode eigenvalue, so the desired mode eigenvalue can be easily determined.This time series approach was tested for a variety of problems including multi-dimensional ones. Numerical results show that the time series approach has strong potential for three dimensional whole reactor core. The eigenvalue ratio can be updated in an on-the-fly manner without storing the nuclear fission source distributions at all previous iteration cycles for the mean subtraction. Lastly, the effects of degenerate eigenvalues are investigated and solutions are provided.