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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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Deep Space: The new frontier of radiation controls
In commercial nuclear power, there has always been a deliberate tension between the regulator and the utility owner. The regulator fundamentally exists to protect the worker, and the utility, to make a profit. It is a win-win balance.
From the U.S. nuclear industry has emerged a brilliantly successful occupational nuclear safety record—largely the result of an ALARA (as low as reasonably achievable) process that has driven exposure rates down to what only a decade ago would have been considered unthinkable. In the U.S. nuclear industry, the system has accomplished an excellent, nearly seamless process that succeeds to the benefit of both employee and utility owner.
Kai Yao, Shengyuan Yan, Cong Chi Tran
Nuclear Technology | Volume 208 | Number 4 | April 2022 | Pages 761-774
Technical Note | doi.org/10.1080/00295450.2021.1947123
Articles are hosted by Taylor and Francis Online.
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.