OPTIMAL FLUX MAP GENERATION THROUGH PARAMETER-ESTIMATION TECHNIQUES

Two methods are presented for optimally calculating spatial distributi ons of neutron flux in a nuclear reactor core. Both techniques, Kalman filtering and maximum likelihood estimation, simultaneously account f or all initial information contained in the nominal core specification s and in-core measurements, as well as all of the uncertainties within the system, to provide a minimum variance estimate of neutron flux. T hese methods resolve discrepancies in the initial information in a sta tistically optimal manner, thereby providing valuable insight into the nature of the optimal solution obtained. Despite radically different algorithms, both methods yield the same minimum variance estimate for the quantity of interest. The algorithms have been successfully tested for one-dimensional axial and two-dimensional x-y flux mapping proble ms with simulated in-core data sets.