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
Latest Magazine Issues
May 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
June 2026
Nuclear Technology
Fusion Science and Technology
Latest News
South Korea looks to Southern and NuScale
This week, the United States and South Korea have taken two steps toward deepening their nuclear partnership through two notable announcements. First, the majority-state owned Korea Hydro & Nuclear Power signed a memorandum of understanding with Birmingham, Ala.–based Southern Nuclear.
Yousef M. Farawila, Daniel R. Tinkler
Nuclear Science and Engineering | Volume 199 | Number 4 | April 2025 | Pages 679-697
Research Article | doi.org/10.1080/00295639.2024.2384220
Articles are hosted by Taylor and Francis Online.
Noise signals obtained from local power range monitors and average power range monitors are routinely used for extracting stability information for boiling water reactors. The stability parameters of decay ratio (DR) and natural frequency are produced by signal processing algorithms. While theoretically a dynamical system like a reactor core composed of coherently coupled components possesses a unique DR, noise measurements from different detectors have been reported in several published works to produce different DRs, creating the impression that a DR is not unique at a given operating state but rather is space dependent. This paper is an attempt to reconcile theory with measurements and resolve the space-dependent DR paradox that was encountered afresh in the course of designing a new high-fidelity online stability monitor. As such, the issue of space dependence could not be overlooked as attributable to variability within the uncertainty of noise analysis algorithms.