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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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Powering the future: How the DOE is fueling nuclear fuel cycle research and development
As global interest in nuclear energy surges, the United States must remain at the forefront of research and development to ensure national energy security, advance nuclear technologies, and promote international cooperation on safety and nonproliferation. A crucial step in achieving this is analyzing how funding and resources are allocated to better understand how to direct future research and development. The Department of Energy has spearheaded this effort by funding hundreds of research projects across the country through the Nuclear Energy University Program (NEUP). This initiative has empowered dozens of universities to collaborate toward a nuclear-friendly future.
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.