Abstract
The hybrid Monte Carlo/deterministic techniques CADIS and FW-CADIS dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been restricted by the availability of computing resources for their preliminary deterministic calculations and the large computer memory requirements of their final Monte Carlo calculations. Three automatic mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding some maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh from the mesh of the deterministic calculations to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to calculate the prompt dose rate throughout the entire ITER experimental facility. Compared to a FW-CADIS calculation with the same weight window map memory requirement, using the three algorithms resulted in a 23.3% increase in the regions where the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled the accurate performance of this difficult global Monte Carlo calculation, which traditionally needed high performance computing, using a FW-CADIS simulation on a regular computer cluster.
