使用ANN进行热中子盾设计,用于BNCT治疗室
Fatemeh S Rasouli1, Atefeh Yahyaee2, S Farhad Masoudi2
1Department of Physics, K.N. Toosi University of Technology, P.O. Box 15875-4416, Tehran, Iran. rasouli@kntu.ac.ir.
Scientific reports
|June 26, 2024
概括
这项研究引入了一种新的聚合物复合物和聚乙烯屏蔽材料,用于中子捕获疗法 (BNCT) 治疗室. 优化的材料有效降低了门后的职业辐射剂量,为传统模拟提供了更快的替代方案.
科学领域:
- 医学物理 医学物理
- 辐射瘤学 辐射瘤学
- 材料科学 材料科学 材料科学
背景情况:
- 职业辐射保护在治疗室中至关重要,特别是在子中子捕获疗法 (BNCT) 等技术中.
- 从光束造型组件 (BSA) 逃逸的中子构成风险,需要对治疗室门进行有效的屏蔽.
研究的目的:
- 为BNCT治疗室门设计和评估一种替代的屏蔽材料.
- 在穿越房间墙壁和迷宫后,有效地吸收来自BSA的热中子.
主要方法:
- 使用Geant4蒙特卡洛代码模拟聚合物复合物和聚乙烯热中子屏蔽.
- 使用人工神经网络 (ANN) 预测中子流量和剂量值,以快速优化参数.
- 使用高斯分布式不确定性测试ANN稳定性.
主要成果:
- 由ANN确定的优化屏蔽材料有效地降低了门后面的辐射剂量,低于职业暴露限值.
- 通过ANN计算,可以同时优化屏蔽参数 (厚度,组成).
- ANN被证明是预测剂量测量结果的可靠和有效工具,超过了耗时的蒙特卡洛模拟.
结论:
- 开发的屏蔽材料为BNCT设施提供了传统屏蔽的可行替代方案.
- 人工神经网络为优化辐射屏蔽设计和预测剂量测量结果提供了一种强大而有效的方法.
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