Cai Yao, Hao Rui, Yu Shaojie, Wang Chang, Hu Guang
China Ship Development and Design Center, Wuhan, 430064, China; School of Nuclear Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
China Ship Development and Design Center, Wuhan, 430064, China.
Appl Radiat Isot. 2020 May;159:109061. doi: 10.1016/j.apradiso.2020.109061. Epub 2020 Feb 14.
Combining the SCE algorithm (Shuffled Complex Evolution), MOEA/D algorithm (Multi-Objective Evolutionary Algorithm based on Decomposition), MCNP program and several prediction models, two multi-objective optimization methods (priori method and posteriori method) for radiation shielding material, which considering the shielding, mass, volume, mechanical and thermal properties are established. The material is in the form of resin matrix composite. The shielding performance of the material is simulated by MCNP program. The mechanical property and thermal property are calculated by some widely used prediction models. Several materials are optimized by the two methods respectively, and comparisons among the materials are made. The results show that, both the two methods could achieve synergistic optimization of shielding, mass, volume, mechanical properties and thermal properties of material. Differently, the priori method only obtains one solution corresponding to its weight values, while the posteriori method obtains the whole Pareto-optimal set. These two methods have their own advantages and disadvantages, which should be selected according to the actual situation.
结合SCE算法（洗牌复合进化算法）、MOEA/D算法（基于分解的多目标进化算法）、MCNP程序和几种预测模型，建立了两种考虑屏蔽、质量、体积、力学和热性能的辐射屏蔽材料多目标优化方法（先验方法和后验方法）。材料为树脂基复合材料形式。材料的屏蔽性能通过MCNP程序模拟。力学性能和热性能通过一些广泛使用的预测模型计算。分别用这两种方法对几种材料进行了优化，并对材料进行了比较。结果表明，这两种方法都能实现材料屏蔽、质量、体积、力学性能和热性能的协同优化。不同的是，先验方法仅获得对应其权重值的一个解，而后验方法获得整个帕累托最优集。这两种方法各有优缺点，应根据实际情况选择。
