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Division Spotlight
Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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!
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Latest News
Four million nuclear jobs by 2050: Who will do them?
Industry leaders from around the globe met this month to discuss the talent development that will be necessary for the long-term success of the nuclear industry.
The International Conference on Nuclear Knowledge Management and Human Resources Development, hosted by the International Atomic Energy Agency, was held in Vienna earlier this month. Discussed there was the agency’s forecast for nuclear capacity to more than double—or hopefully triple—by 2050 and the requirement of more than four million professionals to support the industry.
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.