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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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PR: American Nuclear Society welcomes Senate confirmation of Ted Garrish as the DOE’s nuclear energy secretary
Washington, D.C. — The American Nuclear Society (ANS) applauds the U.S. Senate's confirmation of Theodore “Ted” Garrish as Assistant Secretary for Nuclear Energy at the U.S. Department of Energy (DOE).
“On behalf of over 11,000 professionals in the fields of nuclear science and technology, the American Nuclear Society congratulates Mr. Garrish on being confirmed by the Senate to once again lead the DOE Office of Nuclear Energy,” said ANS President H.M. "Hash" Hashemian.
M. Marseguerra, E. Zio
Nuclear Science and Engineering | Volume 117 | Number 3 | July 1994 | Pages 194-200
Technical Paper | doi.org/10.13182/NSE94-A28534
Articles are hosted by Taylor and Francis Online.
The Boltzmann machine is a general-purpose artificial neural network that can be used as an associative memory as well as a mapping tool. The usual information entropy is introduced, and a network energy function is suitably defined. The network’s training procedure is based on the simulated annealing during which a combination of energy minimization and entropy maximization is achieved.,An application in the nuclear reactor field is presented in which the Boltzmann input-output machine is used to detect and diagnose a pipe break in a simulated auxiliary feedwater system feeding two coupled steam generators. The break may occur on either the hot or the cold leg of any of the two steam generators. The binary input data to the network encode only the trends of the thermohydraulic signals so that the network is actually a polarity device. The results indicate that the trained neural network is actually capable of performing its task. The method appears to be robust enough so that it may also be applied with success in the presence of substantial amounts of noise that cause the network to be fed with wrong signals.