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

Abstract

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.