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Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
Standards Program
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.
Yoshikuni Shinohara, Ritsuo Oguma
Nuclear Science and Engineering | Volume 52 | Number 1 | September 1973 | Pages 76-83
Technical Paper | doi.org/10.13182/NSE73-A23290
Articles are hosted by Taylor and Francis Online.
A simple method of nonlinear filtering is applied to the problem of dynamic reactivity estimation in which the law of reactivity change is assumed to be unknown. The filter is designed based on a system model containing the usual point reactor kinetics equations driven by fictitious white noises and a reactivity state equation. The latter is formulated such that the rate of the reactivity change is a random process, taking account of the unknown reactivity change. The nonlinear filter applied here is a simple modification of the Kalman filter added with a nonlinear feedback loop. The key parameter that determines the filter response is the parameter of the fictitious noise in the reactivity equation which is closely related to the filter gain. The results of the computer simulation and the experiment show that the nonlinear filter can be used to estimate the dynamic reactivity, even under an extremely noisy measurement condition.