Comparison between Equilibrium Cycle and Successive Multicycle Optimization Methods for In-Core Fuel Management of Pressurized Water Reactors.

Abstract

Analyses of an equilibrium cycle are useful for evaluating newly designed fuels, defining an envelope of core operating parameters, and so on. However, generation of a loading pattern for the equilibrium cycle is much more difficult than that of a single cycle. Therefore, a loading pattern optimization code for the equilibrium cycle of pressurized water reactors, OPAL, has been newly developed on the basis of the simulated annealing method. In order to verify the capability of the OPAL code, comparison with successive multicycle optimizations was performed while fixing the number of fresh fuel in each cycle. Through benchmark calculations, it was found that the result of the equilibrium cycle optimization was almost compatible with that of the successive multicycle optimization, when the definition of each objective function was similar. However, successive multicycle optimization includes some ambiguity due to limits on the number of calculated cycles, since it requires much computation time. Consequently, the equilibrium cycle optimization has advantages including the quantitative comparison of the core neutronic performances.

Simultaneous Loading Patterns Optimization for Two Successive Cycles of Pressurized Water Reactors

“…(12) were chosen as shown in Table 4 based on the previous experience in incore optimization calculations. 10,25) Note that in the discharge burnup maximization, the cycle length was implicitly taken into account in the objective function since the discharge burnup for a loading pattern becomes larger when the cycle length is longer.…”

“…Therefore, alternate approaches, i.e., the equilibrium cycle optimization and optimization of batch power sharing, were tried to capture the coupling effect. 25,29) In this paper, simultaneous optimization of two successive cycles (i.e., tandem cycles) will be carried out in PWR. The simulated annealing method is used as an optimization method.…”

“…Several researches were devoted to investigate the coupling effect between cycles and these researches revealed that the coupling effect has significant impact on overall fuel cycle cost. [23][24][25][26][27] In other words, optimum core design for single cycle could be different from the true optimum one that is obtained by the multicycle optimization. For example, in order to reduce number of fresh fuel assemblies in single cycle optimization, core reactivity at end of cycle (EOC) must be increased.…”