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
Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
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
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.
Jaques Reifman, Javier E. Vitela
Nuclear Technology | Volume 106 | Number 2 | May 1994 | Pages 225-241
Technical Paper | Reactor Control | doi.org/10.13182/NT94-A34978
Articles are hosted by Taylor and Francis Online.
The method of conjugate gradients is used to expedite the learning process of feedforward multilayer artificial neural networks and to systematically update both the learning parameter and the momentum parameter at each training cycle. The mechanism for the occurrence of premature saturation of the network nodes observed with the backpropagation algorithm is described, suggestions are made to eliminate this undesirable phenomenon, and the reason by which this phenomenon is precluded in the method of conjugate gradients is presented. The proposed method is compared with the standard backpropagation algorithm in the training of neural networks to classify transient events in nuclear power plants simulated by the Midland Nuclear Power Plant Unit 2 simulator. The comparison results indicate that the rate of convergence of the proposed method is much greater than the standard backpropagation, that it reduces both the number of training cycles and the CPU time, and that it is less sensitive to the choice of initial weights. The advantages of the method are more noticeable and important for problems where the network architecture consists of a large number of nodes, the training database is large, and a tight convergence criterion is desired.