Finding the best fuel assemblies shuffling scheme of ADS for MA transmutation using Dynamic Programming

Abstract

Dynamic Programming is applied to find the best shuffling scheme of ADS, which consists of 54 fuel assemblies and a spallation target of Pb–Bi, and the best scheme is successfully found under different constraints of power peaking factor. In the present problem the average transmutation ratio of MA is maximized under the constraints for effective neutron multiplication factor, discharged fuel burn-up, and power peaking factor. The obtained results show the best fuel shuffling scheme consists of initial unique shuffling pattern and succeeding repetitive patterns for all cases. The repetitive pattern is unique for each constraint of power peaking factor, the best shuffling scheme changes sensitively for the change of constraints. For most best shuffling schemes, fresh fuel is loaded into the 2nd inner row of fuel region, and finally discharged from the inner or outer region because of the constraint of power peaking factor.