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The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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NEA panel on AI hosted at World Governments Summit
A panel on the potential of artificial intelligence to accelerate small modular reactors was held at the World Governments Summit (WGS) in February in Dubai, United Arab Emirates. The OECD Nuclear Energy Agency cohosted the event, which attracted leaders from developers, IT companies, regulators, and other experts.
A. F. Debosscher
Nuclear Science and Engineering | Volume 69 | Number 3 | March 1979 | Pages 354-362
Technical Paper | doi.org/10.13182/NSE79-A19952
Articles are hosted by Taylor and Francis Online.
In the present paper, an exact first-order statistical analysis is given of the power and temperature fluctuations in a nuclear power reactor with temperature feedback, which is perturbed by Gaussian white reactivity noise. Using a new technique, the time-independent Fokker-Planck equation for the two-dimensional power-temperature Markov process is solved in terms of a two-dimensional first-order characteristic function. This characteristic function gives a complete first-order statistical description of the investigated stochastic process and allows for the calculation of the marginal and the combined probability density functions of reactor power and temperature. In addition, a general expression for the moments is derived. Since the underlying reactor model has been extensively used in approximate linearized analyses, a comparison can be made of the exact results obtained in this paper with the earlier results, and the validity of the linear approximation can be delimited in terms of two dimensionless system parameters.