辐射防护2026，Vol.46Issue(2)：106-115,10.
基于天鹰算法与BP神经网络混合模型的X射线柔性材料屏蔽性能优化
Performance optimization of X-ray flexible shielding materials based on a hybrid AO-BP neural network model
摘要
Abstract
The performance optimization of radiation shielding materials remains a central focus in the field of radiation protection.Traditional approaches to shielding material design have relied heavily on extensive experimental data and empirical knowledge,which is not only time-consuming and costly,but also cannot guarantee identification of globally optimal solutions.This study proposes a strategy combining the Aquila·114·Optimizer(AO)with a BP neural network to optimize the composition of X-ray shielding materials and achieve efficient shielding across different X-ray energy segments.Initially,Monte Carlo simulations are employed to establish an X-ray tube model.Functional elements featuring complementary K-absorption edge characteristics are screened via the XCOM program,and Monte Carlo calculations determine the shielding rate for various elemental proportions.Subsequently,a BP neural network is employed to model the non-linear mapping between input parameters(elemental composition)and output parameters(shielding performance).SHAP(SHapley Additive Explanations)interpretability is applied to quantify the contribution of each element to the shielding rate.The AO algorithm is subsequently employed to determine the optimal elemental proportion scheme.Finally,Monte Carlo simulations are utilized for performance testing and comparative analysis of the optimized composition.Results indicate that for the composition W∶Bi∶Gd∶Sm∶SEBS=0.018 8∶0.261 0∶0.058 1∶0.162 1∶0.500 0,a shielding rate of 75.51%is achieved at 100 kV tube voltage,with a material density of 1.600 7 g/cm3.Additionally,an in-depth investigation of optimal functional element proportions for different energy segments was performed.This method demonstrates significant innovation and effectiveness,thus enriching the computational methods for research,development,and application optimization of composite shielding materials.关键词
辐射屏蔽/X射线/AO算法/BP 神经网络/蒙特卡罗/优化设计Key words
radiation shielding/x-ray/aquila optimizer algorithm/BP neural network/Monte Carlo/optimization design分类
能源科技引用本文复制引用
王宇桐,朱伟杰,魏昊,李君,原林,王博宇,刘洋..基于天鹰算法与BP神经网络混合模型的X射线柔性材料屏蔽性能优化[J].辐射防护,2026,46(2):106-115,10.基金项目
西安工程大学大学生创新创业训练计划项目(202510709050) （202510709050）
西安工程大学青年骨干人才支持计划(107020688) （107020688）
陕西省教育厅重点科学研究计划项目(No.24JR071)资助 （No.24JR071）
陕西高校青年创新团队资助. （）
