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
Thermal Hydraulics
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
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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Nuclear Science and Engineering
August 2024
Nuclear Technology
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Latest News
Oklo completes end-to-end demonstration of advanced fuel recycling
Oklo Inc. has announced that it has completed the first end-to-end demonstration of its advanced fuel recycling process as part of an ongoing $5 million project in collaboration with Argonne and Idaho National Laboratories. Oklo’s goal: scaling up its fuel recycling capabilities to deploy a commercial-scale recycling facility that would increase advanced reactor fuel supplies and enhance fuel cost effectiveness for its planned sodium fast reactors.
Jie Lin, Yair Bartal, Robert E. Uhrig
Nuclear Technology | Volume 111 | Number 1 | July 1995 | Pages 46-62
Technical Paper | Nuclear Reactor Safety | doi.org/10.13182/NT95-A35143
Articles are hosted by Taylor and Francis Online.
The importance of automatic diagnostic systems for nuclear power plants (NPPs) has been discussed in numerous studies, and various such systems have been proposed. None of those systems were designed to predict the severity of the diagnosed scenario. A classification and severity prediction system for NPP transients is developed. The system is based on nearest neighbors modeling, which is optimized using genetic algorithms. The optimization process is used to determine the most important variables for each of the transient types analyzed. An enhanced version of the genetic algorithms is used in which a local downhill search is performed to further increase the accuracy achieved. The genetic algorithms search was implemented on a massively parallel supercomputer, the KSR1-64, to perform the analysis in a reasonable time. The data for this study were supplied by the highfidelity simulator of the San Onofre unit 1 pressurized water reactor.