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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.
Yih-Tsuen Wu, A. Berge Gureghian, Budhi Sagar, Richard B. Codell
Nuclear Technology | Volume 104 | Number 2 | November 1993 | Pages 297-308
Technical Paper | Special Issue on Waste Management / Radioactive Waste Management | doi.org/10.13182/NT93-A34891
Articles are hosted by Taylor and Francis Online.
An uncertainty and probabilistic sensitivity study of a hypothetical underground high-level waste (HLW) repository intersected by a vertical fracture or fault and under saturated conditions is presented. Several recently developed probabilistic methods, including the advanced mean value method and the adaptive importance sampling method, are applied to a previously developed one-dimensional analytical model. These probabilistic methods are based on a limit-state formulation and provide an effective means of computing performance probability distribution and probabilitybased random parameter sensitivities. A numerical example related to the transport of 237Np in a system of layered fractured rock is used to illustrate the application of these probabilistic methods for efficient uncertainty and probabilistic sensitivity analyses.