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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
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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
Argonne’s METL gears up to test more sodium fast reactor components
Argonne National Laboratory has successfully swapped out an aging cold trap in the sodium test loop called METL (Mechanisms Engineering Test Loop), the Department of Energy announced April 23. The upgrade is the first of its kind in the United States in more than 30 years, according to the DOE, and will help test components and operations for the sodium-cooled fast reactors being developed now.
Chaung Lin, Jieh-Rern Chang, Suh-Chyn Jenc
Nuclear Science and Engineering | Volume 102 | Number 3 | July 1989 | Pages 283-294
Technical Paper | doi.org/10.13182/NSE89-A27478
Articles are hosted by Taylor and Francis Online.
A multivariable theory is applied to the design of the recirculation and feed water control systems of a boiling water reactor. The nuclear steam supply system simulation model is represented by a set of 14 first-order nonlinear ordinary differential equations. Linearization about a steady-state operating point leads to a linear model. To reduce the computational effort, a sixth-order model is obtained by an optimal order reduction method. A robust controller is designed so that the regulation and tracking capability holds in the presence of certain perturbations and disturbances to the plant. The controller parameters are obtained by the parameter optimization method. The results of simulation show that the control system performs well and has robust stability.