Optimization of axial enrichment distribution for BWR fuels using scoping libraries and block coordinate descent method

Highlights: • An optimization method for axial enrichment distribution in a BWR fuel was developed. • Block coordinate descent method is employed to search for optimal solution. • Scoping libraries are used to reduce computational effort. • Optimization search space consists of enrichment difference parameters. • Capability of the method to find optimal solution is demonstrated. - Abstract: An optimization method has been developed to search for the optimal axial enrichment distribution in a fuel assembly for a boiling water reactor core. The optimization method features: (1) employing the block coordinate descent method to find the optimal solution in the space of enrichment difference parameters, (2) using scoping libraries to reduce the amount of CASMO-4 calculation, and (3) integrating a core critical constraint into the objective function that is used to quantify the quality of an axial enrichment design. The objective function consists of the weighted sum of core parameters such as shutdown margin and critical power ratio. The core parameters are evaluated by using SIMULATE-3, and the cross section data required for the SIMULATE-3 calculation are generated by using CASMO-4 and scoping libraries. The application of the method to a 4-segment fuel design (with the highest allowable segment enrichment relaxed to 5%) demonstrated that the method can obtain an axial enrichment design with improved thermal limit ratios and objective function value while satisfying the core design constraints and core critical requirement through the use of an objective function. The use of scoping libraries effectively reduced the number of CASMO-4 calculation, from 85 to 24, in the 4-segment optimization case. An exhausted search was performed to examine the capability of the method in finding the optimal solution for a 4-segment fuel design. The results show that the method found a solution very close to the optimum obtained by the exhausted search. The number of objective function evaluation (OFV) in the exhausted search is 8707, and the number of OFV in the search using the optimization method is 41. The reduction in OFV shows the efficiency of the optimization method. The optimization designs with more than 4 enriched axial segments were also performed to see if better objective function values can be achieved by having more axial segments.