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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
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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Latest News
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Ji Hyun Lee, Alper Yilmaz, Richard Denning, Tunc Aldemir
Nuclear Technology | Volume 205 | Number 8 | August 2019 | Pages 1035-1042
Technical Paper – Special section on Big Data for Nuclear Power Plants | doi.org/10.1080/00295450.2018.1541394
Articles are hosted by Taylor and Francis Online.
An initiating event that disrupts regular nuclear power plant (NPP) operation can result in a variety of different scenarios as time progresses depending on the response of standby safety systems and operator actions to bring the plant to a safe, stable state, or the uncertainties in accident phenomenology. Depending on the severity of the accident and potential magnitude of release of radioactive material into the environment, off-site emergency response such as evacuation may be warranted. An approach that could be used for real-time emergency guidance to support the declaration of a site emergency and to guide off-site response is presented using observable plant data in the early stages of a severe accident. The approach is based on the simulation of the possible NPP behavior following an initiating event and projects the likelihood of different levels of off-site release of radionuclides from the plant using deep learning (DL) techniques. Training of the DL process is accomplished using results of a large number of scenarios generated with the Analysis of Dynamic Accident Progression Trees/MELCOR/Radiological Assessment System for Consequence Analysis (RASCAL) computer codes to simulate the variety of possible consequences following a station blackout event (similar to the Fukushima accident) for a large pressurized water reactor. The ability of the model to predict the likelihood of different levels of consequences is assessed using a separate test set of MELCOR/RASCAL calculations.