Validation of a PGNAA sensor model for bulk material sorting

分类 蒙特卡罗方法 灵敏度(控制系统) 中子活化分析 工艺工程 过程(计算) 计算机科学 材料科学 环境科学 工程类 电子工程 算法 化学 数学 放射化学 统计 操作系统
作者
Dylan Peukert,Chaoshui Xu,Peter A. Dowd
出处
期刊:Minerals Engineering [Elsevier]
卷期号:217: 108950-108950
标识
DOI:10.1016/j.mineng.2024.108950
摘要

• A detailed model of a PGNAA bulk material sensor was developed. • The model was validated with sensor measurements of sample materials. • The model was able to simulate the PGNAA spectrum and characteristic peaks. • The simulation can decompose the spectrum by process and origin. • The model can aid signal analysis, use evaluation and sensor design. Global mineral demand is forecast to increase significantly to achieve the transition to renewable energy. Greater volumes of ore of lower grade will have to be mined to meet demand. Techniques to process large volumes of low-grade ore efficiently are being investigated to reduce the cost and impact of mining. One technique is to use sensor information to sort mined material, allowing waste to be discarded early in mineral processing. Prompt gamma neutron activation analysis (PGNAA) is a sensing technique that can provide information on the multi-elemental composition of a bulk sample which can be used for bulk material sorting. This paper presents the development of a Monte Carlo simulation model of a PGNAA sensor for bulk sorting using the Geant4 toolkit. The GEOSCAN sensor (Scantech Australia) was used as a case-study to demonstrate the application of the model. The sensor responses for a range of pure mineral samples (Fe 2 O 3 , SiO 2 , S, Na 2 CO 3 and MnO 2 ) were measured to validate the developed model. The sensitivity of the simulation results to the hadronic and electromagnetic physics models used was tested. It was determined that the PGNAA sensor model can reproduce measurements obtained from the GEOSCAN sensor. In particular, the model can provide a good reproduction of the overall spectral shape and the locations of distinct characteristic peaks. The differences between simulated and experimental results are within 30% on average. It was found that the Geant4 HP neutron model best reproduces the activation peaks observed in experimental measurements. Additionally, the PGNAA spectrum was found to be insensitive to the choice of electromagnetic model for the photon interactions. The validated sensor model provides a useful tool for investigating PGNAA sensor applications including a bulk sorting strategy for new materials, sensor calibration, improvements in signal analysis and optimised sensor design.
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