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.
Explore membership for yourself or for your organization.
Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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
Aug 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
September 2025
Nuclear Technology
Fusion Science and Technology
August 2025
Latest News
DOE-NE’s newest fuel consortium includes defense from antitrust laws
The Department of Energy's Office of Nuclear Energy is setting up a nuclear fuel Defense Production Act Consortium that will seek voluntary agreements with interested companies “to increase fuel availability, provide more access to reliable power, and end America’s reliance on foreign sources of enriched uranium and critical materials needed to power the nation’s nuclear renaissance.” According to an August 22 DOE press release, the plan invokes the Defense Production Act (DPA) to give consortium members “defense from antitrust laws when certain criteria are met” and “allow industry consultation to develop plans of action.” DOE-NE is looking for interested companies to join the consortium ahead of its first meeting, scheduled for October 14.
Miltiadis Alamaniotis (Univ of Texas at San Antonio), Asok Ray (Penn State)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 431-439
Monitoring of Boiling Water Rectors (BWRs) is a complex process that requires the use of a numerous sensors and systems. Acquisition of data and the subsequent processing of it accommodate inference making with regard to the state of the reactor system. System identification promotes decision making with regard to operation action taking. In this paper, we present a new method for serially integrating two machine learning tools and more specifically a neural network and a set of algorithms for learning Gaussian processes. Both sets of tools exhibit learning capabilities, and their integration in the current work offers a two-stage learning schema applied to identification of transient states in BWR. In particular, the proposed methodology utilizes the synergism of a set of Gaussian processes with a feedforward neural network for recognizing the type of loss of coolant accident (LOCA) that occurs in the reactor. The methodology is tested on a set of real-world datasets taken from the FIX-II facility. Results demonstrate efficacy of the method to accurately identify the occurring LOCA among three possible states.