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Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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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Jul 2024
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Nuclear Science and Engineering
August 2024
Nuclear Technology
Fusion Science and Technology
Latest News
ARPA-E announces $40 million to develop transmutation technologies for UNF
The Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) announced $40 million in funding to develop cutting-edge technologies to enable the transmutation of used nuclear fuel into less-radioactive substances. According to ARPA-E, the new initiative addresses one of the agency’s core goals as outlined by Congress: to provide transformative solutions to improve the management, cleanup, and disposal of radioactive waste and spent nuclear fuel.
Brent Shumaker, Steven Brewer, Alexander Hashemian, Ryan Kettle
Nuclear Technology | Volume 209 | Number 3 | March 2023 | Pages 390-400
Technical Paper—Instrumentation and Controls | doi.org/10.1080/00295450.2022.2067460
Articles are hosted by Taylor and Francis Online.
This paper presents the results of an ongoing research and development effort to develop an online monitoring (OLM) system to support autonomous microreactor operations. A key component of this work is an evaluation of artificial intelligence (AI) and machine learning (ML) techniques to identify, diagnose, and predict problems with sensors and processes of the reactor. As described herein, selected methods of AI/ML were used to identify and diagnose anomalous sensor and system behaviors using data from a thermal-hydraulic flow loop and from operating nuclear power plants. This work serves to further the state of the art in OLM technologies for nuclear reactor applications and will ultimately result in a comprehensive system to enable OLM of critical structures, systems, components, and processes in microreactors.