Tiantian CUI, Shuyuan ZHANG, Liang SUN, et al. The assessment for the effects of multiple combined variance reduction techniques in shielding computation on an electron irradiation accelerator[J]. Nuclear techniques, 2018, 41(3): 030201
DOI:
Tiantian CUI, Shuyuan ZHANG, Liang SUN, et al. The assessment for the effects of multiple combined variance reduction techniques in shielding computation on an electron irradiation accelerator[J]. Nuclear techniques, 2018, 41(3): 030201 DOI: 10.11889/j.0253-3219.2018.hjs.41.030201.
The assessment for the effects of multiple combined variance reduction techniques in shielding computation on an electron irradiation accelerator
减方差技术是辐射防护、核医学、核探井等应用领域中解决深穿透问题的常用方法。当前减方差技术的研究基本基于简单理论几何模型,缺少在实际复杂模型上的讨论,本文以实际应用的电子辐照加速器整体系统为研究的几何模型,以屏蔽后的剂量为计算目标。比较了电子和不同辐照物质相互作用时产生次级光子能量谱和方向谱的差异,并以蒙特卡罗程序MCNP5(Monte Carlo N Particle Transport Code)为平台详细研究对比了几何分裂、源偏倚、指数衰减、分步输运、DXTRAN球和权窗等常见减方差技术在单独使用和不同组合使用下的实际效果,评估了具有实用性减方差技术的选择和组合。结果表明:辐照物质对次级光子的方向谱影响很大,出于建模有效性考虑,几何模型应尽量贴合实际,不能过分简化;分步输运和源偏倚相比于其它常规减方差技术可以更好地降低计算误差,它们和几何分裂、DXTRAN球和指数衰减组合使用时,可以进一步降低计算误差,有效提高结果的可信度;权窗相对于常规减方差技术具有更好的计算效率和客观性,以权窗、分步输运和源偏倚为基础,再组合其他减方差技术,可以很好地解决实际应用中复杂模型的深穿透问题。
Abstract
Background
2
Variance reduction is a common method to resolve the problems in deep penetration application such as radiation shielding
medical physics and well-logging. Currently
the study of the variance reduction techniques is based on simple theoretical geometric model
lacking the discussion on complex practical applications.
Purpose
2
This paper aims to find an optimized combined variance reduction technique in deep penetration application on the practical complex model.
Methods
2
With an electron irradiation accelerator as the model
this paper studied the effects of combined variance reduction techniques on MCNP5 (Monte Carlo N Particle Transport Code) platform
including geometry splitting
biasing the source
exponential transform
step-step transform
DXTRAN and weight window.
Result
2
The results showed that the irradiation products had a great influence on the angular distribution of spectrum of the new source
and the geometric model should not be overly simplified. Compared with other variance-reducing techniques
the step-step transform and biasing the source efficiency reduced the relative error and could get a better calculation efficiency combined with geometric splitting
exponential transform and DXTRAN. Weight window had better computation efficiency and more objectivity.
Conclusion
2
The step-step transform and biasing the source
combined with other variance reduction techniques can resolve deep penetration problem in complex practical application based on weight window.
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