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Division Spotlight
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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
Wisconsin lawmakers push nuclear support
A joint resolution under consideration in the Wisconsin legislature aims to declare and promote the state’s support for nuclear power and willingness to deploy additional sources.
Yochan Kim, Jinkyun Park, Mary Presley
Nuclear Science and Engineering | Volume 197 | Number 11 | November 2023 | Pages 2787-2799
PSA 2021 Paper | doi.org/10.1080/00295639.2022.2118481
Articles are hosted by Taylor and Francis Online.
With the development of new digital human-machine interfaces, many discussions in the nuclear industry have focused on the human factors issues that arise from the interfaces. To quantitatively characterize the effects of the interfaces on human reliability, we collected empirical data from a full-scope simulator of the APR1400 nuclear power plant using the Human Reliability Extraction (HuREX) framework. From the numerous variables in the collected data describing the contexts of the performance influencing factors (PIFs), including crew experience, task complexity, and procedure quality, the significant variables were identified by three techniques comprising both qualitative and quantitative analyses. Based on the selected variables, the nominal error probabilities and PIF multipliers were then estimated by logistic regression analysis. This paper interprets the meanings of the estimates and discusses the advantages of the employed variable selection techniques.