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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.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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
Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
Michael Thompson (Univ of Tennessee, Knoxville), Benjamin Jordan (Centrus Energy), Jamie Coble (Univ of Tennessee, Knoxville)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 1267-1274
Greater situational awareness of plant conditions is necessary to move the current fleet of nuclear power facilities away from costly periodic maintenance activities. Sensed data provide the indicators of plant and equipment condition; however, these instrumentation and transmitters are themselves subject to aging and degradation over time. Online monitoring methods have long been proposed to assess the calibration status of sensors based on the data collected during normal plant operation. Auto-associative kernel regression models (AAKR) are commonly applied to predict the “expected” sensor value, and statistical hypothesis tests or thresholding algorithms are used to determine if the measured value agrees with the expectation. AAKR models work well for stationary operation of systems, but these models may not be as well suited for systems that undergo normal operational transients, as we expect to see in small modular reactors, advanced reactors, and many fuel cycle facilities. This paper presents an alternative approach to detection and diagnostics of sensor degradation and anomalies based on generalized singular value decomposition (GSVD) in computational linear algebra. The proposed method is demonstrated on experimental data collected on a two loop forced-flow water loop, but the approach is expected to be more generally applicable to a variety of nuclear facilities and to equipment and components beyond sensor suites.