论文标题

巴西多功能反应器中的中子成像中心的随机建模

Stochastic modeling of a neutron imaging center at the Brazilian Multipurpose Reactor

论文作者

de Oliveira, Luiz P., Souza, Alexandre P. S., Genezini, Frederico A., Santos, Adimir dos

论文摘要

中子成像是一种用于分析各种样本(例如考古或工业材料结构)的非破坏性技术。近几十年来,技术进步对中子成像技术产生了很大的影响,这意味着从使用膜(2D)到具有数字处理(3D)的现代层析成像系统的演变。 5 MW研究核反应堆IEA-R1位于巴西的Pesquisas de PesquisasEncorgéticasE核核(IPEN),拥有一种中子成像仪器,具有$ 1.0 \ times 10^{6} $ $ $ $ $ n/cm^{2} s $在样品位置。 IEA-R1已有60多年的历史了,包括成像在内的巴西Neutron Science的未来将扩展到一个名为巴西多功能反应堆(RMB,葡萄牙首字母缩写)的新设施,该设施将很快建造。新的反应堆将在中子国家实验室放置一套仪器,包括Neinei的中子成像设施。受作者最近的作品的启发,我们通过随机蒙特卡洛模拟对Neinei仪器进行建模。我们研究了中子通量的中子成像技术参数($ l/d $比)的敏感性,并将结果与​​Neutra(PSI),Antares(FRM II),BT2(NIST)和Dingo(Opal)仪器的数据进行比较。结果是有希望的,并为未来的改进提供了途径。

Neutron imaging is a non-destructive technique for analyzing a wide class of samples, such as archaeological or industrial material structures. In recent decades, technological advances have had a great impact on the neutron imaging technique, which has meant an evolution from simple radiographs using films (2D) to modern tomography systems with digital processing (3D). The 5 MW research nuclear reactor IEA-R1, which is located at the Instituto de Pesquisas Energéticas e Nucleares (IPEN) in Brazil, possesses a neutron imaging instrument with $1.0 \times 10^{6}$ $n/cm^{2}s$ in the sample position. IEA-R1 is over 60 years old and the future of neutron science in Brazil, including imaging, will be expanded to a new facility called the Brazilian Multipurpose Reactor (RMB, Portuguese acronym), which will be built soon. The new reactor will house a suite of instruments at the Neutron National Laboratory, including the neutron imaging facility, viz., Neinei. Inspired by recent author's works, we model the Neinei instrument through stochastic Monte Carlo simulations. We investigate the sensitivity of the neutron imaging technique parameter ($L/D$ ratio) with the neutron flux, and the results are compared to data from the Neutra (PSI), Antares (FRM II), BT2 (NIST) and DINGO (OPAL) instruments. The results are promising and provide avenues for future improvements.

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