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
Feb 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
March 2026
Nuclear Technology
February 2026
Fusion Science and Technology
January 2026
Latest News
Mirion announces appointments
Mirion Technologies has announced three senior leadership appointments designed to support its global nuclear and medical businesses while advancing a company-wide digital and AI strategy. The leadership changes come as Mirion seeks to advance innovation and maintain strong performance in nuclear energy, radiation safety, and medical applications.
Y. W. Wang, B. S. Pei, C. H. King, S. C. Lee
Nuclear Technology | Volume 89 | Number 2 | February 1990 | Pages 217-226
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT90-A34348
Articles are hosted by Taylor and Francis Online.
A method based on noise analysis techniques that can be applied to the identification of two-phase flow patterns in nuclear reactors is proposed. The identifying criterion, the high-frequency contribution fraction (HFCF), offers new potential to the in-core recognition of two-phase flow patterns. By analyzing 76 sets of signals acquired from a research nuclear reactor where two-phase flow patterns are generated in an in-core air/water loop, the typical signal, autocorrelogram, and spectrum of each flow pattern are demonstrated and evaluated. The identification success rate is 87 or 93%, depending on whether churn flow is counted. A method to improve the identification rate is also presented. In comparison with our previous work, this study demonstrates that the fluctuation characteristics above 10 Hz are induced by two-phase flow itself and are independent of the driving source; thus, it is adequate to apply the HFCF to the identification of two-phase flow patterns. The present study shows that it is possible to identify two-phase flow patterns by HFCF values.