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Division Spotlight
Reactor Physics
The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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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.
Fan Zhang, J. Wesley Hines, 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 1370-1379
The industry targeted cyber-attacks has increased in the recent years. In addition, digitalizing the instrumentation and control brings new cybersecurity challenges to the supervisory control and data acquisition (SCADA) system; therefore, the cybersecurity of the SCADA system should be enhanced. This paper proposed an auto-associative kernel regression (AAKR) data-driven model based on network flow data for early attack detection of SCADA system. This model is integrated to the cyber-attack detection system (CADS) proposed before to provide multi-layer defense and better coverage of detectable cyber-attacks. For generating data for the research, a real-time SCADA system test bed was built at the University of Tennessee. It contains a physically modeled thermal-hydraulic part for a typical two-loop nuclear system; a SCADA system based on LabVIEW and a programmable logic controller (PLC); a local area network (LAN)-based cyber network which enables cyber-attacks and data collection. The normal data set and two abnormal data sets fed into the proposed auto-associative kernel regression (AAKR) model were collected under the normal operation, man in the middle (MITM) and denial of service (DoS) attack scenarios, respectively. The result shows that the proposed AAKR model is able to detect the MITM and DoS attacks effectively with almost no false alarms.
