An iterative prediction method for designing the moderator used for the boron neutron capture therapy
An iterative prediction method for designing the moderator used for the boron neutron capture therapy
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设计用于硼中子俘获疗法的慢化剂的迭代预测方法
DOI：
10.1002/mp.15339
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发表时间：
2021-12-07
期刊：
影响因子：
3.8
通讯作者：
Yang, Yigang
中科院分区：
文献类型：
--
作者：
Zhang, Ruiqin;Yu, Yangyi;Yang, Yigang
目的为了进行慢中子的相关研究，必须对快中子进行定模并使其转移到所需的能区。方法提出一种迭代预测方法，利用反射矩阵R和透射矩阵T表征所有材料的中子输运特性，从而绕过耗时的Monte Carlo模拟，预测用于硼中子俘获治疗（BNCT）的慢化剂的性能，包括超热中子通量以及快中子和γ射线的剂量。为了在庞大的参数空间中找到最优解，采用了结合透射矩阵和反射矩阵的遗传算法。结果经过70次循环迭代，BNCT慢化器的超热中子注量率比文献报道的经验优化慢化器高出近80%。与蒙特卡罗方法相比，该方法具有计算时间短、统计误差小等优点。结论矩阵遗传算法（GAM）可以在较大的参数空间中找到最优解，且不需要进行穷举计算。这是一种很有前途的设计方法，用于热中子或超热中子用途的慢化剂。
Purpose To conduct research related to slow neutrons, fast neutrons must be mode-rated and shifted to the desired energy region. Methods In this research, an iterated prediction method, in which the neutron transportation properties of all materials were characterized by a reflection matrix, R, and a transmission matrix, T, was proposed to bypass a time-consuming Monte Carlo simulation and predict the performance of the moderator, including the epithermal neutron flux and the dose of fast neutrons and gamma rays, used for boron neutron capture therapy (BNCT). To find the optimal solution in the huge parameter space, a genetic algorithm combined with transmission and reflection matrices was utilized. Results The results showed that a 70-loop iteration was able to find a design for the moderator of BNCT with almost 80% higher epithermal neutron flux per kilowatt than that of the empirically optimized moderator that was previously reported in the literature. Compared with the Monte Carlo method, this method had the advantage of reducing the calculation time and statistical errors. Conclusion The genetic algorithm with matrices (GAM) method can be used to find an optimal solution in a huge parameter space without brute-force calculations. It could be a promising method for designing the moderator for thermal or epithermal neutron usages.