DERMAGA - An alternative tool to generate random patterned-channel-age in CANDU fuel management analyses part II: Robustness against varying basic pattern size

The instantaneous power distribution in the core can be calculated when the actual bundle-wise burnup distribution is known. In the light water reactor technology where batch fuelling practice is employed, the snapshot of power distribution during the cycle could be easily obtained by monitoring and simulating the core from the beginning to the end of the fuel cycle. Such calculation is more challenging for CANDU reactors. Considering the fact that CANDU utilizes the on-power refuelling to compensate for the reduction in reactivity due to fuel burnup, in CANDU fuel management analyses, snapshots of power and burnup distributions can be obtained by simulating and tracking reactor operation over an extended period using various tools such as the *SIMULATE module of the reactor fuelling simulation program (RFSP) code. However, for some studies, such as an evaluation of a conceptual design of a next generation CANDU reactor, the preferred approach to obtain a snapshot of the power distribution in the core is based on the patterned-channel-age model implemented in the *INSTANTAN module of the RFSP code. The objective of this approach is to obtain a representative snapshot of core conditions quickly and use such snapshot to perform additional reactor-physics related analyses. Presently such patterns could be generated by a program called RANDIS which is implemented within the *INSTANTAN module. An alternative approach called DERMAGA (DistributEd RandoM Age generator using Genetic Algorithm) has been developed to derive the patterned-channel-age model where an optimization algorithm is utilized to find patterns which produce representative power distributions in the core. Within DERMAGA, the genetic algorithm technique has been utilized as the optimization engine to find a quasi-optimal patterned-channel-age. It has been demonstrated that DERMAGA is a viable alternative tool to produce representative snapshots of daily core configuration. In the present paper which is Part II of a two-part paper, the robustness of DERMAGA is tested against various different sizes of basic grid used for generating the random patterned-channel-age.