Fuel management optimization using genetic algorithms and expert knowledge

Journal Article · Sun Sep 01 00:00:00 EDT 1996 · Nuclear Science and Engineering

OSTI ID:379815

DeChaine, M D; Feltus, M A ^[1]

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1. Pennsylvania State Univ., University Park, PA (United States)

The CIGARO fuel management optimization code based on genetic algorithms is described and tested. The test problem optimized the core lifetime for a pressurized water reactor with a penalty function constraint on the peak normalized power. A bit-string genotype encoded the loading patterns, and genotype bias was reduced with additional bits. Expert knowledge about fuel management was incorporated into the genetic algorithm. Regional crossover exchanged physically adjacent fuel assemblies and improved the optimization slightly. Biasing the initial population toward a known priority table significantly improved the optimization.

• OSTI ID: 379815
• Journal Information: Nuclear Science and Engineering, Vol. 124, Issue 1; Other Information: PBD: Sep 1996
• Country of Publication: United States
• Language: English

Related Subjects

21 NUCLEAR POWER REACTORS AND ASSOCIATED PLANTS
99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
FUEL MANAGEMENT
C CODES
PWR TYPE REACTORS
PERFORMANCE TESTING
REACTOR CORES
REACTOR FUELING
EXPERT SYSTEMS