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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
Oklo to collaborate with Atomic Alchemy on isotope production
Fast reactor developer Oklo, which recently went public on the New York Stock Exchange, announced on May 13 that it has signed a memorandum of understanding with Atomic Alchemy to cooperate on the production of radioisotopes for medical, energy, industry, and science applications.
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.