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Understanding and investigating the relationships between geometrical errors and lost particles in MCNP
Fusion Engineering and Design ( IF 1.9 ) Pub Date : 2020-10-01 , DOI: 10.1016/j.fusengdes.2020.111975
Davide Laghi , Marco Fabbri , Raul Pampin , Alfredo Portone

Abstract Generating Constructive Solid Geometry (CSG) ready for MCNP input using automated programs, and the use of universe structures, may give raise to geometrical inconsistencies leading to numerical phenomena known as lost particles, which perturb the statistical reliability of the transport solution. In the context of the reference nuclear analysis models developed for ITER, there is a need to better understand these phenomena, define a sufficiently explicit way to test the models, and provide clear and uniform parameters indicating their technical quality and reliability in terms of geometrical errors. Using a source able to generate an isotropic and uniform fluence inside its closed surface, it was possible to derive a relationship between source’s surface area, lost particles rate and error size. These results were verified with multiple MCNP runs and good agreement was found between simulations results and analytical predictions. This work allows defining more explicit and uniform procedures to debug for lost particles, and provides a way to grade model quality based on objective parameters, like the size of errors, instead of using others that heavily depend on the setup on which the simulation was run.

中文翻译:

理解和研究 MCNP 中几何误差和丢失粒子之间的关系

摘要 使用自动化程序生成准备用于 MCNP 输入的构造实体几何 (CSG) 和宇宙结构的使用,可能会引起几何不一致,导致称为丢失粒子的数值现象,这会扰乱传输解决方案的统计可靠性。在为 ITER 开发的参考核分析模型的背景下,需要更好地理解这些现象,定义一种足够明确的方法来测试模型,并提供清晰统一的参数,表明其技术质量和几何误差方面的可靠性. 使用能够在其封闭表面内产生各向同性和均匀注量的源,可以推导出源表面积、丢失颗粒率和误差大小之间的关系。这些结果通过多次 MCNP 运行进行了验证,并且在模拟结果和分析预测之间发现了良好的一致性。这项工作允许定义更明确和统一的程序来调试丢失的粒子,并提供一种基于客观参数(如错误大小)对模型质量进行分级的方法,而不是使用严重依赖于运行模拟的设置的其他参数.
更新日期:2020-10-01
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