Monte Carlo Model of the Large Modular Array for Positron Emission Particle Tracking

Monte Carlo Model of the Large Modular Array for Positron Emission Particle Tracking
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正电子发射粒子跟踪大型模块化阵列的蒙特卡罗模型

DOI:
10.1109/access.2023.3255505
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发表时间:
2023
期刊:
影响因子:
3.9
通讯作者:
Herald M
Herald M
中科院分区:
计算机科学3区
文献类型:
--
作者:
Herald M

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正电子发射粒子跟踪(PEPT)是一种非侵入性技术,用于研究学术界和工业界感兴趣的流体,颗粒和多相系统。PEPT采用位置敏感的辐射探测器来记录符合的伽马射线,并跟踪离散源的运动。伯明翰大学正电子成像中心(PIC)建造了一个模块化探测器阵列,即大型模块化阵列(LaMA),以实现定制探测器几何形状。为了在实验之前估计LaMA的性能特性,帮助开发优化的相机几何形状,并确定理想的PEPT示踪剂特性,创建了LaMA的Monte Carlo模型,并随后通过实验测量进行验证。验证是通过比较的空间分辨率和计数率响应以下的国家电气制造商协会(NEMA)的行业标准协议。值得注意的是,该模型的脉冲处理链是自主校准,以匹配实验测量使用最近开发的技术,应用进化算法。结果表明,验证模型的模拟空间分辨率与实验匹配在5%以内。此外,总计数率、真实计数率和损坏计数率的平均误差为3.41%。这种校准的探测器模型加强了PIC的建模能力。为了促进未来的研究,该模型已通过PIC的GitHub存储库公开提供。
Positron emission particle tracking (PEPT) is a non-invasive technique used to study fluid, granular, and multi-phase systems of interest to academia and industry. PEPT employs position-sensitive radiation detectors to record gamma rays in coincidence and track the movement of discrete sources. A modular detector array, the Large Modular Array (LaMA), has been constructed at the University of Birmingham’s Positron Imaging Centre (PIC) to enable custom detector geometries. To estimate the LaMA’s performance characteristics prior to experimentation, assist in developing optimised camera geometries, and determine ideal PEPT tracer characteristics a Monte Carlo model of LaMA is created and subsequently validated with experimental measurements. Validation is achieved through comparisons of the spatial resolution and count-rate response following the National Electrical Manufacturers Association (NEMA) industry standard protocol. Notably, the model’s pulse-processing chain is autonomously calibrated to match experimental measurements using a recently developed technique which applies an evolutionary algorithm. The results show the simulated spatial resolution of the validated model matches the experiment to within 5%. Additionally, the total, true, and corrupted count-rates are reproduced to a mean error of 3.41%. This calibrated detector model strengthens the PIC’s modelling capabilities. To facilitate future research, this model has been made publicly available through the PIC’s GitHub repository.
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