基于遗传算法的中子屏蔽材料组分优化研究

基于快速非支配排序遗传算法NSGA-Ⅱ,开展了多目标屏蔽优化设计研究,建立了中子复合屏蔽材料组分的自动优化设计程序。以屏蔽剂量和材料密度最小化为目标,以聚乙烯、铅、硼、锂、铁、铝等材料均匀混合组成30 cm厚平板屏蔽结构为例,验证了优化算法程序的有效性。将基于遗传算法的屏蔽优化方法与设计人员的经验相结合,可更高效地实现多目标屏蔽优化设计。

Optimization research on neutron shielding material component based on genetic algorithm

Based on the fast non-dominated sorting genetic algorithm NSGA-II, multi-objective optimization of shielding design was studied, and automatic optimization design code for composite neutron shielding material component was developed. Aiming at the minimum shielding dose and material density, the effectiveness of the code is demonstrated by an example of 30 cm thick slab shield, which is composed of polyethylene, lead, steel, aluminum, boron and lithium homogeneously. Combining the shielding optimization method based on genetic algorithm and the experience of designer, multi-objective optimization of shielding design can be achieved more efficiently.