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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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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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ARG-US Remote Monitoring Systems: Use Cases and Applications in Nuclear Facilities and During Transportation
As highlighted in the Spring 2024 issue of Radwaste Solutions, researchers at the Department of Energy’s Argonne National Laboratory are developing and deploying ARG-US—meaning “Watchful Guardian”—remote monitoring systems technologies to enhance the safety, security, and safeguards (3S) of packages of nuclear and other radioactive material during storage, transportation, and disposal.
Felix C. Difilippo
Nuclear Science and Engineering | Volume 142 | Number 2 | October 2002 | Pages 140-149
Technical Paper | doi.org/10.13182/NSE02-A2294
Articles are hosted by Taylor and Francis Online.
The analysis of the fluctuations of signals coming from detectors in the vicinity of a subcritical assembly of fissile materials is commonly used for the control and safeguard of nuclear materials and might be used for the surveillance of an accelerator driven system. One of the stochastic techniques is the measurement of the probability distributions of counts in time intervals t (gates); the departure of the ratio of the variance and the mean value with respect to 1 (the correlation) is directly related to the amount of fissile material and its subcriticality. The measurement of this correlation is affected by dead-time effects due to count losses because of the finite-time resolution of the detection system. We present a theory that allows (a) the calculation of the probability of losing n counts (P(n)) in gate t, (b) the definition of experimental conditions under which P(2) << P(1), and (c) a methodology to correct the measured correlation because of losing one count in any gate. The theory is applied to the analysis of experiments performed in a highly enriched subcritical assembly.
