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 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jun 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
August 2026
Nuclear Technology
July 2026
Fusion Science and Technology
Latest News
Launching into tomorrow: NRIC guides new era of research and deployment
In June 2025, the Department of Energy announced the Reactor Pilot Program, an authorization pathway that allowed reactor developers to partner with the DOE to get first-of-a-kind (FOAK) reactors built and tested. Soon after, the DOE rolled out a complementary Fuel Line Pilot Program, which aimed to fast-track fuel projects. In all, 20 projects were accepted into the new programs.
C. H. King, M. S. Ouyang, B. S. Pei, Y. W. Wang
Nuclear Technology | Volume 82 | Number 2 | August 1988 | Pages 211-226
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT88-A34108
Articles are hosted by Taylor and Francis Online.
A new technique of identifying the flow regimes of air/water two-phase flow in a vertical pipe is proposed. This technique is based on analyzing the statistical characteristics of the static and differential pressure signals by an optimum modeling method. The major concept of the optimum modeling method is to fit the two-phase flow pressure noise by autoregressive moving average (ARMA) models with an optimization technique. The results show that it is possible to identify the flow patterns from a set of “flow regime indices,” such as dynamic signature, order of dominant dynamics mode, and order of ARMA model. A computer code based on these indices has been built on an IBM-PC/XT microcomputer to perform two-phase flow pattern identification. The success probability of this code is ∼85% on the data base collected from our experimental work. The experimental data points are also indicated in a Taitel flow map and excellent matching has been shown, except for some points around the flow regime transition boundaries. These discrepancies are due to the subjective categorization of the flow regimes.