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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.
James F. Harrison
Nuclear Technology | Volume 83 | Number 3 | December 1988 | Pages 310-324
Technical Paper | Fifth International Retran Meeting / Heat Transfer and Fluid Flow | doi.org/10.13182/NT88-A34144
Articles are hosted by Taylor and Francis Online.
An assessment of RETRAN’s ability to provide best-estimate reference information for the qualification of full-scope power plant training simulators is provided. Analyses that compare RETRAN predictions to plant data or to test facility data are summarized. The relationship between the RETRAN qualification studies and the simulator test matrix presented in Electric Power Research Institute NP-4243, Analytic Simulator Qualification Methodology, and the requirements of ANSI/ANS-3.5 are discussed. Thirty-one boiling water reactor transient analyses and 50 pressurized water reactor analyses have been evaluated. The evaluation shows that RETRAN models have experienced essentially all of the “dynamic states” required for the qualification of power plant training simulators. The rating for the magnitude, timing, and trend measures indicates that the predictions using RETRAN models are either completely acceptable or acceptable with some reservations most of the time. The magnitude performance varies depending on the type of event, whereas the trend and timing performance is nearly the same for all event types. The ratings for the RETRAN transient predictions show that RETRAN models are capable of predicting the important system parameters with the fidelity required for the qualification of training simulators.