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The human factor in licensing and operating the next generation of nuclear plants
As human factors specialists working at the intersection of human performance and nuclear operations, we are witnessing one of the nuclear sector’s most significant transitions in decades. The emergence of small modular reactors, microreactors, and other advanced designs is reshaping the industry’s landscape. Digital instrumentation and controls, passive safety systems, and increased automation are creating opportunities for greater safety margins and more flexible operation. These same features also fundamentally redefine what it means to “operate” a nuclear plant. Interactions among human roles, automation, and passive systems shape how people maintain awareness, exercise judgment, and intervene when necessary. These developments affect both operational realities and the regulatory foundations on which nuclear safety is built.
Meng Yue, Lap-Yan Cheng, Robert A. Bari
Nuclear Technology | Volume 162 | Number 1 | April 2008 | Pages 26-44
Technical Paper | Reactor Safety | doi.org/10.13182/NT08-A3931
Articles are hosted by Taylor and Francis Online.
A Markov model approach is developed for the evaluation of proliferation resistance (PR) of nuclear energy systems. The focus of this study is to create a high-fidelity probabilistic assessment model that better represents nuclear energy systems. Both extrinsic and intrinsic barriers associated with the energy systems are considered. Modeling uncertainty and safeguards false alarms, composite safeguards approaches, concealment, and human performance are particularly discussed in detail and incorporated in the Markov model. These features are anticipated to have significant impacts on PR assessment. The Markov model approach is adapted to a hypothetical example sodium fast reactor (ESFR) system using physically meaningful parameters that can be obtained from physical processes. Development of metrics for six PR measures is discussed. Computation of the PR measures using the Markov model of the ESFR system is illustrated. The results obtained in this study demonstrate applicability and effectiveness of the Markov model approach in the PR assessment.