Forward-weighted CADIS method for global variance reduction

The FW-CADIS method for optimizing global distributions has been developed, and initial testing on a model of an entire PWR facility has been performed. The method has also been applied to two other large problems, including an array of spent fuel storage casks, as described in a companion paper [7]. In all applications to dale, excellent results have been achieved. The method requires two approximate discrete ordinates calculations {one forward and one adjoint) to generate consistent source biasing and weight window parameters for the subsequent Monte Carlo simulation and docs not require any modifications to existing Monte Carlo codes. Although more testing and thorough analysis of results is still needed, the potential of this method for optimizing global distributions, including energy-dependent flux distributions, as well as semi-global distributions, such as response at multiple localized detectors or spectra, appears very promising. Furthermore, this method should be suitable for a large range of problems, including the use of Monte Carlo for depletion.