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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.
Te-Chuan Wang, Min Lee
Nuclear Technology | Volume 206 | Number 3 | March 2020 | Pages 414-427
Technical Paper | doi.org/10.1080/00295450.2019.1653152
Articles are hosted by Taylor and Francis Online.
MAAP5 is an integral severe accident analysis program that simulates the responses of a light water reactor power plant during a severe accident. This program has been used extensively for probabilistic safety assessments, verification and validation of mitigation actions specified in severe accident management guidelines, and source term quantification. In this study, the uncertainty of in-vessel hydrogen generation predicted by the MAAP5 code was quantified. The surrogate plant that was analyzed is the Lungmen Nuclear Power Station of the Taiwan Power Company. The plant employs an advanced boiling water reactor. We performed sensitivity studies to identify the important model parameters that affect the target output parameters. A range and distribution were assigned to these parameters on the basis of experimental results and expert judgment. The number of input parameters in the analysis was 27. Multiple MAAP5 calculations were performed with an input combination generated from Latin hypercube sampling. The calculation results were analyzed parametrically and nonparametrically to determine the 95th percentile with the 95% confidence level value of the amount of in-vessel hydrogen generation. The Pearson correlation coefficient was used to determine the effect of the model parameters on the target output parameters. The analysis results provide guidance for code applications. The only parameters that pass the threshold of 0.362 for hydrogen generation in the core are FCO and TCLMAX. For hydrogen generation in the lower plenum, FOXBJ is the only input parameter that passes the threshold.