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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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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Hash Hashemian: Visionary leadership
As Dr. Hashem M. “Hash” Hashemian prepares to step into his term as President of the American Nuclear Society, he is clear that he wants to make the most of this unique moment.
A groundswell in public approval of nuclear is finding a home in growing governmental support that is backed by a tailwind of technological innovation. “Now is a good time to be in nuclear,” Hashemian said, as he explained the criticality of this moment and what he hoped to accomplish as president.
D. Mandelli, C. Smith, T. Riley, J. Nielsen, A. Alfonsi, J. Cogliati, C. Rabiti, J. Schroeder
Nuclear Technology | Volume 193 | Number 1 | January 2016 | Pages 161-174
Technical Paper | Special Issue on the RELAP5-3D Computer Code | doi.org/10.13182/NT14-142
Articles are hosted by Taylor and Francis Online.
The existing fleet of nuclear power plants is in the process of having its lifetime extended and having the power generated from these plants increased via power uprates and improved operations. In order to evaluate the impact of these factors on the safety of the plant, the Risk-Informed Safety Margin Characterization (RISMC) pathway aims to provide insights to decision makers through a series of simulations of the plant dynamics for different initial conditions and accident scenarios. This paper presents a case study in order to show the capabilities of the RISMC methodology to assess the impact of power uprate of a boiling water reactor system during a station blackout accident scenario. We employ a system simulator code, RELAP5-3D, coupled with RAVEN, which performs the stochastic analysis. Our analysis is performed by (a) sampling values from a set of parameters from the uncertainty space of interest, (b) simulating the system behavior for that specific set of parameter values, and (c) analyzing the outcomes from the set of simulation runs.