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The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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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.
R. Accorsi, M. Marseguerra, E. Padovani, E. Zio
Nuclear Science and Engineering | Volume 132 | Number 3 | July 1999 | Pages 326-336
Technical Paper | doi.org/10.13182/NSE99-A2067
Articles are hosted by Taylor and Francis Online.
In real, complex plants, a sensitivity analysis of the effects that variations in the plant inputs and design parameters have on the outputs is of great importance both from the point of view of productivity and of safety. To a first approximation, sensitivity analysis consists of estimating the partial derivatives of the outputs with respect to the varied quantities. These derivatives cannot be obtained on the real plant directly since the effects of all the involved variables are intermixed. Therefore, one has to resort to suitable computational models and algorithms.A new neural network approach that aims at creating a differentiable copy of the plant is proposed. A feature of the method is that the data for network training are collected with the system in nominal operation: This represents, indeed, a fundamental constraint for all risky plants, for which unrestrained playing is definitely not recommended. The sensitivity coefficients (partial derivatives) thereby obtained are applied for the regulation of the reactivity of a simulated pressurized water reactor in response to changes in the electric load at the power grid, so as to maintain the average temperature of the water in the reactor core at a constant value.