γ-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various challenges that contribute to statistical and systematic uncertainties in the estimated isotopics. Furthermore, these methods typically require numerous pre-processing steps, and have only been rigorously tested in laboratory settings with limited shielding. Here, in this work, we examine the application of a number of machine learning based regression algorithms as alternatives to conventional approaches for analyzing γ-ray spectroscopy data in the Emergency Response arena. This approach not only eliminates many steps in the analysis procedure, and therefore offers potential to reduce this source of systematic uncertainty, but is also shown to offer comparable performance to conventional approaches in the Emergency Response Application.
Khatiwada, Ajeeta, et al. "Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra." Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 1054, Jun. 2023. https://doi.org/10.1016/j.nima.2023.168409
Khatiwada, Ajeeta, Klasky, Marc Louis, Lombardi, Marcie, Matheny, Jason Ray, & Mohan, Arvind Thanam (2023). Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra. Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, 1054. https://doi.org/10.1016/j.nima.2023.168409
Khatiwada, Ajeeta, Klasky, Marc Louis, Lombardi, Marcie, et al., "Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra," Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment 1054 (2023), https://doi.org/10.1016/j.nima.2023.168409
@article{osti_1992274,
author = {Khatiwada, Ajeeta and Klasky, Marc Louis and Lombardi, Marcie and Matheny, Jason Ray and Mohan, Arvind Thanam},
title = {Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra},
annote = {γ-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various challenges that contribute to statistical and systematic uncertainties in the estimated isotopics. Furthermore, these methods typically require numerous pre-processing steps, and have only been rigorously tested in laboratory settings with limited shielding. Here, in this work, we examine the application of a number of machine learning based regression algorithms as alternatives to conventional approaches for analyzing γ-ray spectroscopy data in the Emergency Response arena. This approach not only eliminates many steps in the analysis procedure, and therefore offers potential to reduce this source of systematic uncertainty, but is also shown to offer comparable performance to conventional approaches in the Emergency Response Application.},
doi = {10.1016/j.nima.2023.168409},
url = {https://www.osti.gov/biblio/1992274},
journal = {Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment},
issn = {ISSN 0168-9002},
volume = {1054},
place = {United States},
publisher = {Elsevier},
year = {2023},
month = {06}}
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1992274
Report Number(s):
LA-UR-23-20010
Journal Information:
Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, Journal Name: Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment Vol. 1054; ISSN 0168-9002
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 312, Issue 1-2https://doi.org/10.1016/0168-9002(92)90148-W
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 368, Issue 2https://doi.org/10.1016/0168-9002(95)00663-X
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 484, Issue 1-3https://doi.org/10.1016/S0168-9002(01)01962-3
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 369, Issue 2-3https://doi.org/10.1016/S0168-9002(96)80068-4
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 401, Issue 1https://doi.org/10.1016/S0168-9002(97)01023-1
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 401, Issue 2-3https://doi.org/10.1016/S0168-9002(97)01058-9
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 422, Issue 1-3https://doi.org/10.1016/S0168-9002(98)01110-3
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 443, Issue 1https://doi.org/10.1016/S0168-9002(99)01005-0
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 530, Issue 3https://doi.org/10.1016/j.nima.2004.04.229
Kangas, Lars J.; Keller, Paul E.; Siciliano, Edward R.
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 587, Issue 2-3https://doi.org/10.1016/j.nima.2008.01.065
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 598, Issue 2https://doi.org/10.1016/j.nima.2008.09.035
Shaban, Sameh E.; Hazzaa, M. H.; El-Tayebany, R. A.
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 916https://doi.org/10.1016/j.nima.2018.10.008
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 927https://doi.org/10.1016/j.nima.2019.02.023