@article{chang_meric_sudac_nad_obhodas_hou_zhang_gardner_2019, title={Implementation of the Monte Carlo Library Least-Squares (MCLLS) approach for quantification of the chlorine impurity in an on-line crude oil monitoring system}, volume={155}, ISSN={["0969-806X"]}, DOI={10.1016/j.radphyschem.2018.05.012}, abstractNote={Prompt gamma-ray neutron activation analysis (PGNAA) has been widely used for elemental analysis of bulk samples as it provides an on-line, rapid and non-destructive means of performing such analysis. The Monte Carlo Library Least-Squares (MCLLS) approach is one of the methods for quantitative analysis providing elemental weight fractions via an assumption that the total prompt gamma-ray spectrum is a linear combination of the contributions from the individual prompt gamma-ray spectra of the sample constituents. For the generation of prompt gamma-ray libraries of each constituent, a specific purpose Monte Carlo code system called Center for Engineering Applications of Radioisotopes Coincidence Prompt Gamma-Ray (CEARCPG) is utilized. In this work, the focus was on detecting and measuring chlorine impurity in crude oil samples, i.e. trace amounts of chlorine. A preliminary study investigating the feasibility of PGNAA method in conjunction with the MCLLS approach for measuring trace amounts of chlorine in oil samples was performed. For this purpose, an extended version of the MCLLS approach, the so-called MCLLSX approach, was proposed and applied for the quantitative analysis. The results presented in this paper prove the feasibility of the proposed approach.}, journal={RADIATION PHYSICS AND CHEMISTRY}, author={Chang, Hao Ping and Meric, Ilker and Sudac, Davorin and Nad, Karlo and Obhodas, Jasmina and Hou, Guojing and Zhang, Yan and Gardner, Robin P.}, year={2019}, month={Feb}, pages={197–201} }
 @article{zhang_jia_gardner_shan_zhang_hou_chang_2018, title={A distance correction method for improving the accuracy of particle coal online X-ray fluorescence analysis - Part 1: Theoretical dependence of XRF intensity on the distance}, volume={147}, ISSN={["0969-806X"]}, DOI={10.1016/j.radphyschem.2017.07.005}, abstractNote={During online X-ray fluorescence (XRF) measurement, the distance from XRF spectrometer to the sample surface always changes due to the rough surface textures of pulverized coal, resulting in changes in the X-ray fluorescent intensity and inaccuracy of online XRF measurement. To solve the impact of the sample's rough surface textures on the measurement accuracy, the theory and validity details of the dependence of XRF intensity on the distance as well as the comparison of the formula derivation and experimental verification were elaborated in the present research. A typical XRF calculation model has been built for theoretical derivation. The expression of the relationship between the XRF intensity and the distance from XRF spectrometer to sample surface was derived, where the variation of the distance influenced five physical phenomena: (1) absorption of X-rays by the air, (2) irradiated surface area of the samples, (3) changes in exit angle, (4) changes in solid angle and (5) absorption of X-ray fluorescence by the air. The intensities of the Fe Kα spectral lines in iron were calculated and agreed with the experiments very well, indicating that the expression of the dependence was accurate. The dependence of X-ray fluorescence intensity on the distance is the theoretical basis of the distance correction method to improve the accuracy of online XRF analysis techniques in industrial processes.}, journal={RADIATION PHYSICS AND CHEMISTRY}, author={Zhang, Yan and Jia, Wen Bao and Gardner, Robin and Shan, Qing and Zhang, Xin Lei and Hou, Guojing and Chang, Hao Ping}, year={2018}, month={Jun}, pages={118–121} }
 @article{zhang_jia_gardner_shan_zhang_hou_chang_2017, title={A distance correction method for improving the accuracy of particle coal online X-ray fluorescence analysis - Part 2: Method and experimental investigation}, volume={141}, ISSN={["0969-806X"]}, DOI={10.1016/j.radphyschem.2017.07.004}, abstractNote={The distance from X-Ray Fluorescence (XRF) spectrometer to sample surface always changes with the different coal's particle sizes, resulting in the inaccuracy of online XRF measurement. To improve the accuracy of particle coal online XRF analysis, a distance correction method was established elaborated by iteration, which was based on the relationship between the XRF intensity and the distance. In order to verify the effectiveness of this method, five different particle size coal samples with same components have been measured by the online XRF analyzer directly above the conveyor belt, in the meanwhile, the distances between XRF spectrometer and samples’ surface were obtained by a laser rangefinder. The results showed that the average distances are decreased with decreasing the particle size. By comparing the results of before and after applying the distance correction method, we demonstrated that the measurement accuracy of online XRF analysis for particle coal can be significantly increased. The distance correction method can be used for the development of online XRF analysis techniques applicable for real-time industrial processes.}, journal={RADIATION PHYSICS AND CHEMISTRY}, author={Zhang, Yan and Jia, Wen Bao and Gardner, Robin and Shan, Qing and Zhang, Xin Lei and Hou, Guojing and Chang, Hao Ping}, year={2017}, month={Dec}, pages={235–238} }