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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
First astatine-labeled compound shipped in the U.S.
The Department of Energy’s National Isotope Development Center (NIDC) on March 31 announced the successful long-distance shipment in the United States of a biologically active compound labeled with the medical radioisotope astatine-211 (At-211). Because previous shipments have included only the “bare” isotope, the NIDC has described the development as “unleashing medical innovation.”
Emil Wingstedt (IFE), Olli Saarela (VTT Technical Research Centre of Finland)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 721-732
Data reconciliation is a commonly used technique for correcting random errors in measurement data in the process industry. The technique uses models describing the mutual relationships of process variables related to available measurements. These models are based on knowledge of process physics. Measurement readings are adjusted so that especially mass and energy balances described by the model match. The technique has proven effective in reducing measurement uncertainties. The paper presents a Monte Carlo study of error propagation in data reconciliation of the turbine section of a VVER 440 nuclear power plant. Uncertainties in model parameters describing turbine dry efficiencies and the quality of steam exiting the steam generators are considered in addition to measurement noise. The impact of these factors on estimated reactor thermal power is evaluated, both individually and as joint impacts. For both the measurement signals and the plant parameters, the resulting effect on the uncertainty of thermal power is lower than the 2% uncertainty for reasonable levels of added noise. These results support the use of data reconciliation for reducing the uncertainty in thermal power.