Comparison of global variance reduction techniques for Monte Carlo radiation transport simulations of ITER

It is known that a priori information on the distribution of neutron fluxes around a neutron transport model can improve the computational efficiency of Monte Carlo transport calculations. The uncertainty lies in finding a method which obtains this information as fast and effortlessly as possible. A number of global variance reduction techniques were tested on the ITER reference neutronics model for their applicability for performing large three-dimensional transport simulations for ITER. Among these, we propose a new method which is computationally fast and efficient in determining the a priori flux information. The new method, known as MAGIC, was found to perform well achieving an efficiency 74 times that of an analogue run; the next most efficient was FW-CADIS, performing 48 times better than analogue.