In-core fuel management with biased multiobjective function optimization

The capability of biased multiobjective function optimization has been adde d to the Westinghouse Electric Company's (Westinghouse's) Advanced Loading Pattern Search code (ALPS). The search process, given a user-defined set of design constraints, proceeds to minimize a global parameter called the tot al value associated with constraints compliance (VACC), an importance-weigh ted measure of the deviation from limit and/or margin target. The search pr ocess takes into consideration two equally important user-defined factors w hile minimizing the VACC, namely, the relative importance of each constrain t with respect to the others and the optimization of each constraint accord ing to its own objective function. Hence, trading of margin-to-design limit s from where it is abundantly available to where it is badly needed can now be accomplished. Two practical methods are provided to the user for input of constraints and associated objective functions. One consists of establis hing design limits based on traditional core design parameters such as asse mbly/pin burnup, power, or reactivity. The second method allows the user to write a program, or script, to define a logic not possible through ordinar y means. This method of script writing was made possible through the applic ation resident compiler feature of the technical user language integration processor (tulip), developed at Westinghouse. For the optimization problems studied, ALPS not only produced candidate loading patterns (LPs) that met all of the conflicting design constraints, but in cases where the design ap peared to be over constrained gave a wide range of LPs that came very close to meeting all the constraints based on the associated objective functions .