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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.
Ki-Seob Sim, Ho Chun Suk, Young Ku Yoon
Nuclear Technology | Volume 99 | Number 3 | September 1992 | Pages 351-365
Technical Paper | Nuclear Fuel Cycle | doi.org/10.13182/NT92-A34719
Articles are hosted by Taylor and Francis Online.
The KFGR-T computer model has been developed to predict transient fission gas release from UO2fuel with an emphasis on the nonequilibrium behavior of fission gas bubbles. It takes into account the relevant physical processes generally considered by other workers, as well as migration of fission gas bubbles through channels formed by the extension of dislocations to grain boundaries during the transient heatup stage, grain growth/grain-boundary sweeping during the isothermal annealing stage at high temperatures, and gas release through intergranular cracking. This computer model is applied to calculate transient fission gas releases, and the calculated values are compared with the results of out-of-pile experiments performed with UO2 fuel base-irradiated to burnups in the range of 18 to 35 MW·d/kg U. The absolute values and the trends of the fission gas releases calculated with the KFGR-T model are in good agreement with the experimental data. A parametric study is also done to investigate the sensitivity of the model to variables such as initial grain size, heating rate, temperature gradient, and initial gas concentration, and these results are compared with the sensitivity of other models.