کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1741830 1017419 2006 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Two stochastic optimization algorithms applied to nuclear reactor core design
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
Two stochastic optimization algorithms applied to nuclear reactor core design
چکیده انگلیسی

Two stochastic optimization algorithms conceptually similar to Simulated Annealing are presented and applied to a core design optimization problem previously solved with Genetic Algorithms. The two algorithms are the novel Particle Collision Algorithm (PCA), which is introduced in detail, and Dueck's Great Deluge Algorithm (GDA). The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak factor in a three-enrichment-zone reactor, considering restrictions on the average thermal flux, criticality and sub-moderation. Results show that the PCA and the GDA perform very well compared to the canonical Genetic Algorithm and its variants, and also to Simulated Annealing, hence demonstrating their potential for other optimization applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Progress in Nuclear Energy - Volume 48, Issue 6, August 2006, Pages 525–539
نویسندگان
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