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  This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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  April 3–5, 2025
  Albuquerque, NM|The University of New Mexico
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  April 2025
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  General Kenneth Nichols and the Manhattan Project
  Nichols
  The Oak Ridger has published the latest in a series of articles about General Kenneth D. Nichols, the Manhattan Project, and the 1954 Atomic Energy Act. The series has been produced by Nichols’ grandniece Barbara Rogers Scollin and Oak Ridge (Tenn.) city historian David Ray Smith. Gen. Nichols (1907–2000) was the district engineer for the Manhattan Engineer District during the Manhattan Project.
  As Smith and Scollin explain, Nichols “had supervision of the research and development connected with, and the design, construction, and operation of, all plants required to produce plutonium-239 and uranium-235, including the construction of the towns of Oak Ridge, Tennessee, and Richland, Washington. The responsibility of his position was massive as he oversaw a workforce of both military and civilian personnel of approximately 125,000; his Oak Ridge office became the center of the wartime atomic energy’s activities.”
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Human error is an important factor leading to nuclear power plant (NPP) accidents. The increasing of the amount of information improves the operators’ human error probability (HEP) in the digital main control room of NPPs. Human reliability analysis (HRA) is considered to be an effective method to reduce human error. The Cognitive Reliability and Error Analysis Method (CREAM) is one of the widely accepted HRA methods. However, there are shortcomings that weaken the applicability of this method. Therefore, this research proposes a fuzzy CREAM method based on a combination of fuzzy logic theory and the CREAM method. The study considers the weight of common performance conditions (CPCs) and constructs a logical relationship between CPCs and control modes. Finally, the effectiveness of the proposed method is determined using a widely accepted method to validate the evaluation results. The validated results showed that the evaluation result has a consistency between the fuzzy CREAM method and the traditional CREAM method. They indicated that the fuzzy CREAM method can obtain reliable HEP.