ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Division Spotlight
Reactor Physics
The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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!
Latest Magazine Issues
Jul 2024
Jan 2024
Latest Journal Issues
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.
Yong Xu, Yunze Cai, Lin Song
Nuclear Technology | Volume 209 | Number 7 | July 2023 | Pages 929-962
Critical Review | doi.org/10.1080/00295450.2023.2169042
Articles are hosted by Taylor and Francis Online.
The condition assessment of equipment in nuclear power plants (NPPs) could provide essential information for operation and maintenance decisions, which would have a significant impact on improving the safety and economy of NPPs. To date, substantial work has been conducted on the condition assessment based on machine learning for NPP equipment. To provide a comprehensive overview for researchers interested in developing machine learning methods for NPP equipment condition assessment, this critical review presents a detailed literature survey on state-of-the-art research and identifies challenges for future study. Valuable information is presented, including major failure modes, data sources, maintenance strategies, and the relationship between equipment lifetime, assessment technology, and maintenance strategy. Following the typical lifetime of NPP equipment for condition assessment, current works in this domain are categorized into anomaly detection, remaining useful life prediction, and fault detection and diagnosis. The techniques and methodologies adopted in the literature are summarized from each aspect. In particular, the in-depth NPP equipment condition assessment survey based on deep learning methods is presented. In addition, we elaborate on current issues, challenges, and future research directions for the condition assessment of equipment in NPPs. These directions we believe will pave the way for equipment condition assessment.