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Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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Christmas Night
Twas the night before Christmas when all through the houseNo electrons were flowing through even my mouse.
All devices were plugged in by the chimney with careWith the hope that St. Nikola Tesla would share.
Chenhao Zeng, Wanchang Lai, Jinge Zhou, Hongjian Lin, Xiaojie Feng, Yongping Yu, Runqiu Gu, Shangqing Sun, Jinfei Wu
Nuclear Technology | Volume 209 | Number 4 | April 2023 | Pages 549-559
Technical Paper | doi.org/10.1080/00295450.2022.2133515
Articles are hosted by Taylor and Francis Online.
We address the performance of airborne gamma detection systems equipped with a NaI(Tl) detector to monitor radionuclides in specific areas. In particular, we analyze the use of the fast singular value decomposition (FSVD) algorithm to improve the nuclide recognition ability of the system and effectively trace radioactivity in a complex background environment. We first present a theoretical analysis of the FSVD algorithm and illustrate the nuclide recognition algorithm step by step. The core of the algorithm is singular value decomposition and parameter estimation based on a Gaussian Markov linear regression model. From the estimated values of the parameters, information about radionuclides can be effectively extracted. We assume the presence of a strong background due to a high concentration of 222Rn and its progeny, which is simulated using GEANT4. By adding trace elements of 131I and 137Cs and changing the relative emissivity, the ratio of the total energy peak count of 131I and 137Cs to the background environment interval count of the corresponding 222Rn and its progeny are controlled. Assuming a counting ratio equal to 0.005, the FSVD algorithm is still able to effectively discriminate the presence of a small number of nuclides, reflecting very excellent recognition ability. Finally, based on data from an airborne gamma detection system in a self-control radon chamber, the FSVD algorithm is employed to recognize the trace of 137Cs nuclides in a strong radon background. A DURRIDGE RAD7 radon measuring instrument is used to monitor the radon concentration in the radon chamber. The actual measurement results show that the FSVD algorithm can effectively detect 137Cs nuclides.
