MULTI-OBJECTIVE SARAPAN AND DERMAGA ALGORITHMS FOR GENERATING RANDOM PATTERNED-CHANNEL-AGE IN CANDU FUEL MANAGEMENT ANALYSES


37th Annual CNS Conference - 2017 June 04-07

Presented at:
37th Annual CNS Conference
2017 June 04-07
Location:
Niagara Falls
Session Title:
1A5 - Reactor and Radiation Physics (I)

Authors:
D. Kastanya (Candesco Division of Kinectrics Inc.)
  

Abstract

In CANDU fuel management analyses, snapshots of power and burnup distributions can be obtained by either simulating and tracking the reactor operation over an extended period using various tools such as the reactor fueling simulation program (RFSP) code or by using the patterned-channel-age model in the *INSTANTAN module of the RFSP code. The patterned-channel-age is typically generated using the RANDIS program. Two optimization-based algorithms for creating patterned-channel-ages called SARAPAN (simulated-annealing based) and DERMAGA (genetic-algorithm based) have recently been developed. The multi-objective variant of these algorithms are presented in this paper where the maximum bundle and channel powers of the resulting core snapshot are simultaneously minimized. Results presented in this paper demonstrate that these algorithms are viable alternative to the RANDIS program.

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