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Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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New laws offer nuclear industry incentives for existing power plant uprates
This year, the U.S. nuclear industry received a much-needed economic boost that could help preserve operating nuclear power plants and incentivize upgrades that extend their lifespan and power output.
Signed into law in 2022, the Inflation Reduction Act offers production tax credits (PTCs) for existing nuclear power plants and either PTCs or investment tax credits (ITCs) for new carbon-free generation. These credits could make power uprates—increasing the maximum power level at which a commercial plant may operate—a much more appealing option for utilities.
Jaques Reifman, John C. Lee
Nuclear Science and Engineering | Volume 107 | Number 4 | April 1991 | Pages 291-314
Technical Paper | doi.org/10.13182/NSE91-A23793
Articles are hosted by Taylor and Francis Online.
A pattern recognition algorithm has been developed for systematic generation of shallow knowledge for nuclear power plant transient diagnostics. The algorithm involves feature selection and pattern discovery. The selection of N best features is attained by discarding redundant and nondiscriminatory features. An entropy minimax algorithm is used to discover the patterns by searching an N-dimensional feature space, populated with transient events of the data base, to locate subspaces that discriminate among the event classes. These patterns are then represented as production rules for diagnostics. A series of approximations have been implemented in the algorithm to handle the discovery of patterns in multidimensional space. We have also developed a perturbation algorithm within the entropy minimax framework to update the patterns in an incremental fashion as new data are obtained. The Midland Nuclear Power Plant Unit 2 simulator is used to generate 144 single-failure events. Based on these events, 25 production rules are generated, representing a two-level hierarchical knowledge structure of single-failure events along the critical safety function approach. These rules represent the common characteristics of time-varying features over the diagnostic time, thereby providing diagnostic capability at any time during the transient.