Miller T J
AWE, Aldermaston, Reading, Berkshire, UK.
J Radiol Prot. 2009 Sep;29(3):385-92. doi: 10.1088/0952-4746/29/3/003. Epub 2009 Aug 18.
Previous studies have shown that automated radioactive waste assay techniques, such as segmented gamma scanner (SGS) and automated qualitative and quantitative (AQ2), have severely underestimated fissile material due to either the malfunction or absence of appropriate lump correction routines. This paper examines the application of manual techniques, such as Monte Carlo N particle (MCNP) and spectral non-destructive assay platform (SNAP) software, to lump corrections in plutonium (Pu), enriched uranium (EU) and depleted uranium (DU) waste streams. Excellent results have been obtained when comparing MCNP with SNAP and applying the SNAP lump correction routine to a range of simulated and typical wastes containing various Pu and EU lump sizes. It has been concluded that the need for lump corrections was relatively rare and usually apparent from abnormal gamma ray peak area ratios, since most AWE waste streams are only lightly shielded.
先前的研究表明,自动放射性废物分析技术,如分段伽马扫描仪(SGS)和自动定性定量(AQ2),由于适当的块状物校正程序出现故障或缺失,严重低估了裂变材料。本文研究了手动技术,如蒙特卡罗N粒子(MCNP)和光谱无损分析平台(SNAP)软件,在钚(Pu)、浓缩铀(EU)和贫铀(DU)废物流块状物校正中的应用。将MCNP与SNAP进行比较,并将SNAP块状物校正程序应用于一系列含有各种钚和浓缩铀块状物尺寸的模拟和典型废物时,取得了优异的结果。得出的结论是,块状物校正的需求相对较少,而且通常从异常的伽马射线峰面积比中可以明显看出,因为大多数原子武器 Establishment(AWE)废物流仅轻度屏蔽。