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
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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
Dec 2025
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
January 2026
Nuclear Technology
December 2025
Fusion Science and Technology
November 2025
Latest News
AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
Masaharu Kitamura, Kunihiko Matsubara, Ritsuo Oguma
Nuclear Science and Engineering | Volume 70 | Number 1 | April 1979 | Pages 106-110
Technical Note | doi.org/10.13182/NSE79-A18934
Articles are hosted by Taylor and Francis Online.
The feasibility of reactor noise analysis by autoregressive (AR) modeling is studied from the viewpoint of system identifiability. A condition is derived in which only a part of the identified model becomes meaningful. A practical checking method termed “RRV checking” is proposed, with which the occurrence of the condition is recognized a posteriori for the estimated AR model. This method is applied to AR models obtained by processing the experimental data from the Japan Power Demonstration Reactor II. These models would have been discarded from a conventional viewpoint, since some parts of the model showed physically implausible characteristics. It is verified that the RR V checking method and the empirical evaluation of the usability of the model resulted in the same conclusion about the acceptability of the parts of the models. The processes evaluated to be identifiable from the reactor noise are the response of the fuel temperature to the neutron density and the response of the steam control valve to the reactor pressure. The present method is particularly useful if a priori knowledge about the dynamics of the objective process is limited before the identification experiment.