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Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
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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.
Aldo Dall'Osso
Nuclear Science and Engineering | Volume 154 | Number 2 | October 2006 | Pages 241-246
Technical Paper | doi.org/10.13182/NSE06-A2630
Articles are hosted by Taylor and Francis Online.
The accuracy of a neutronics model depends not only on the validity of the equations that are solved but also on the quality of the cross-section model. This last is currently constituted by a set of correlations, the parameterized tables, relating the data of the neutronics problem to the local conditions. The more the correlations represent the local conditions, the more the results will be accurate. For a simulation model, this means that the results will be closer to the measurements. The goal of the data identification method presented is to solve a constrained inverse problem and to obtain the parameters of some further correlations that will enhance the accuracy of the results. The constraint imposed minimizes the error committed in solving the diffusion equation, using as reference the results of a more accurate computer code or the measurements performed for in-core flux maps. Some purely numerical examples and an application in conjunction with in-core measurements illustrate the method.