Nuclear Fuel Management Optimization Using Genetic Algorithms
- 1 July 1995
- journal article
- research article
- Published by Taylor & Francis in Nuclear Technology
- Vol. 111 (1) , 109-114
- https://doi.org/10.13182/nt95-a35149
Abstract
The code independent genetic algorithm reactor optimization (CIGARO) system has been developed to optimize nuclear reactor loading patterns. It uses genetic algorithms (GAs) and a code-independent interface, so any reactor physics code (e.g., CASMO-3/SIMULATE-3) can be used to evaluate the loading patterns. The system is compared to other GA-based loading pattern optimizers. Tests were carried out to maximize the beginning of cycle keff for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIGARO system performed well, increasing the keff after lowering the peak power. Tests of a prototype parallel evaluation method showed the potential for a significant speedup.Keywords
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