遗传算法在CANDU堆燃料管理中应用的研究

提出了在CANDU堆中应用遗传算法优选换料通道策略，并集成了BP人工神经网络用于CANDU堆堆芯参数预测，预测结果的评价值作为遗传算法的适应值。应用遗传算法和BP神经网络优化模型，研制了CANDU堆燃料管理通道优选程序GAREFUEL。使用换料通道优选程序GAREFUEL和CANDU堆燃料管理程序FMPHWR进行了360天换料模拟。计算结果表明：优选得到的换料通道能够满足堆芯参数限制，GAREFUEL具有快速高效的通道优选能力。

Application of Genetic Algorithm in CANDU Reactor In-core Fuel Management

A strategy, using genetic algorithm (GA) to optimize and select the CANDU reactor refueling channels, is proposed in this paper. A back-propagation artificial neural network (BPANN) is incorporated to predict the core parameters, and the evaluation of the predicted results is taken as the fitness of the GA. GAREFUEL, a refueling channel selection code based on the GA and BPANN, is developed. The refueling simulation is performed using the GAREFUEL and FMPHWR for 360 days. The numerical results show that the selected refueling channels can meet the core parameter limits and GAREFUEL has superior efficiency and speed in selecting the refueling channels.