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在模拟的双能放射系统中研究四种材料歧视算法

M Ghaebi¹, M Tajik¹, R Azimirad²

¹School of Physics, Damghan University, P.O. Box 36716-41167, Damghan, Iran.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine

|July 5, 2023

概括

这项研究模拟了双能X射线放射和评估材料分辨算法. 该R-T算法在识别石墨,,钢和等材料方面表现出卓越的性能,特别是在薄样品中.

科学领域:

医学成像物理医学成像物理
材料科学材料科学材料科学
计算物理计算物理

背景情况:

双能X射线放射是材料差异化的一个有价值的技术.
准确的物质区分对于各种应用,包括安全和工业检查至关重要.
评估不同的材料歧视算法对于优化放射系统至关重要.

研究的目的:

模拟使用MCNPX代码的双能X射线放射系统.
使用四种不同的算法,获得和比较石墨,,钢和的材料区分曲线.
确定在双能放射学中对材料进行歧视的最有效算法,特别是对于较低样本厚度的样本.

主要方法:

模拟使用MCNPX代码的双能X射线放射系统.
对石墨,,钢和的材料歧视曲线的生成.
评估了四个算法:log-log,R-T,r-θ和α-α2.

主要成果:

与日志日志算法相比,R-T,r-θ和α₁-α₂算法在材料歧视方面表现出优异的性能.
材料歧视曲线显示,在较低样本厚度的样本中,重叠较少.
R-T算法被证明是一个更适合的选择,用于材料歧视在双能量放射系统,特别是薄材料.

结论:

在双能X射线放射学中,R-T,r-θ和α₁-α₂算法对于材料歧视是有效的.
R-T算法为材料的区分提供了优势,特别是在处理由于减少曲线重叠的低厚样品时.
这项研究为在双能放射学中选择最佳算法提供了有价值的见解,以提高材料识别.

关键词:

算法算法是一种算法.双重能源 - 双重能源实质性歧视是什么?放射学放射学放射学放射学模拟模拟是为了模拟.这是X射线.

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