ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Division Spotlight
Nuclear Nonproliferation Policy
The mission of the Nuclear Nonproliferation Policy Division (NNPD) is to promote the peaceful use of nuclear technology while simultaneously preventing the diversion and misuse of nuclear material and technology through appropriate safeguards and security, and promotion of nuclear nonproliferation policies. To achieve this mission, the objectives of the NNPD are to: Promote policy that discourages the proliferation of nuclear technology and material to inappropriate entities. Provide information to ANS members, the technical community at large, opinion leaders, and decision makers to improve their understanding of nuclear nonproliferation issues. Become a recognized technical resource on nuclear nonproliferation, safeguards, and security issues. Serve as the integration and coordination body for nuclear nonproliferation activities for the ANS. Work cooperatively with other ANS divisions to achieve these objective nonproliferation policies.
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!
Latest Magazine Issues
Apr 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
May 2025
Nuclear Technology
April 2025
Fusion Science and Technology
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.
Joon-Eon Yang, Tae-Yong Sung, Youngho Jin
Nuclear Technology | Volume 132 | Number 3 | December 2000 | Pages 352-365
Technical Paper | Reactor Safety | doi.org/10.13182/NT00-A3149
Articles are hosted by Taylor and Francis Online.
Up to now, the optimization of surveillance test intervals (STIs) is performed at the system level. In other words, the STI of a system is optimized considering only the conditions related to that system. For instance, the STI of an emergency diesel generator (EDG) is determined considering only the availability of an EDG and the costs related to the changed STI. However, such an approach can cause problems when the effects of each system's optimized STI are combined. That is, the core damage frequency can increase to a level that cannot be accepted by the regulatory body when the STIs optimized at the system level are all adopted together. In this paper, STIs of the systems are optimized at the plant level based on the simplified probabilistic safety assessment (PSA) model of a pressurized water reactor. The PSA model includes most of the important safety systems. It is a nonlinear and multimodal optimization problem with constraints that it optimizes the STIs of various systems based on the PSA model at the plant level. Most conventional optimization techniques have difficulties in handling such multimodal and nonlinear optimization problems. Therefore, we applied a genetic algorithm to the optimization of STIs. The genetic algorithms guarantee the global optimum and find the solution very effectively. In addition, the fault trees used in PSA have some limitations in representing the real world; i.e., in estimating the unavailability of standby systems and the effects of maintenance strategies. So, the analytical unavailability model is implemented to overcome such limits of the conventional fault tree approach. The analytical unavailability model enables us to accurately estimate the effect of a maintenance strategy on the unavailability of systems. The optimized STIs based on the conventional fault tree and the analytical unavailability model are compared.