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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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
ARG-US Remote Monitoring Systems: Use Cases and Applications in Nuclear Facilities and During Transportation
As highlighted in the Spring 2024 issue of Radwaste Solutions, researchers at the Department of Energy’s Argonne National Laboratory are developing and deploying ARG-US—meaning “Watchful Guardian”—remote monitoring systems technologies to enhance the safety, security, and safeguards (3S) of packages of nuclear and other radioactive material during storage, transportation, and disposal.
David L. Aumiller, Michael J. Meholic
Nuclear Science and Engineering | Volume 184 | Number 3 | November 2016 | Pages 453-462
Technical Paper | doi.org/10.13182/NSE16-42
Articles are hosted by Taylor and Francis Online.
COBRA-IE is a three-field subchannel analysis code under development at the Bettis Atomic Power Laboratory. The analysis code is being developed as a general-purpose thermal-hydraulic analysis tool with an emphasis on use in an integrated code system for analyzing postulated large-break loss-of-coolant accidents.
The overall accuracy of programs such as COBRA-IE is tied to the ability to predict void fraction. As such, a comprehensive assessment has been made using one-dimensional void fraction data. The results of this assessment are provided in this paper. The assessment utilizes data from nine different experimental facilities. It includes data from air-water and steam-water facilities, heated flow, adiabatic flow, subcooled boiling, saturated boiling, cocurrent upflow, and cocurrent downflow. Approximately 1100 data points are evaluated and included in this assessment. Overall, COBRA-IE was able to predict the void fraction with an average error (predicted − experimental) of less than 0.04. Plots describing the relationship between the error in the prediction and parameters such as pressure and flow are also provided.