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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.
Jiankai Yu, Hyunsuk Lee, Hanjoo Kim, Peng Zhang, Deokjung Lee
Nuclear Technology | Volume 206 | Number 5 | May 2020 | Pages 728-742
Technical Paper | doi.org/10.1080/00295450.2019.1677107
Articles are hosted by Taylor and Francis Online.
The coupled neutronics–thermal-hydraulic simulation of the Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS) Cycle 1 depletion has been performed by the Monte Carlo–based multiphysics coupling code system MCS/CTF. MCS/CTF is a cyclewise pi-card iteration-based inner-coupling code system that couples the subchannel thermal-hydraulic code CTF as a thermal-hydraulic solver in the Monte Carlo neutron transport code MCS. MCS has been developed by the Computational Reactor Physics and Experiment Lab group at the Ulsan National Institute of Science and Technology for the full-core analysis of large-scale commercial light water reactors with high fidelity at the engineering level. With the high-fidelity performance of MCS, the quarter-core pinwise depletion simulation for the BEAVRS Cycle 1 benchmark has been conducted with thermal-hydraulic feedback including fuel temperature, coolant temperature, and coolant density. Moreover, the MCS internal one-dimensional thermal-hydraulic solver TH1D (MCS/TH1D) has been utilized as the reference. On one hand, the simulated results of the criticality boron concentration and axially integrated assemblywise detector signals were compared with measured data. On the other hand, the comparisons of power, fuel temperature, coolant temperature, and density are also presented in this paper.