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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.
William Boyd, Adam Nelson, Paul K. Romano, Samuel Shaner, Benoit Forget, Kord Smith
Nuclear Technology | Volume 205 | Number 7 | July 2019 | Pages 928-944
Regular Technical Paper | doi.org/10.1080/00295450.2019.1571828
Articles are hosted by Taylor and Francis Online.
High-fidelity deterministic transport codes require highly accurate multigroup cross sections (MGXS). Monte Carlo is increasingly cited as a reactor-agnostic approach to MGXS generation since it is unconstrained by the engineering-based approximations that limit the applicability of deterministic MGXS generation tools. This paper introduces a new framework that uses the OpenMC Monte Carlo code to generate MGXS for use in multigroup transport codes. The openmc.mgxs module is built atop OpenMC’s Python application programming interface to process tally data output by the OpenMC executable. This paper validates the module to generate MGXS that enable the multigroup OpenMOC transport code to compute eigenvalues to within 50 pcm and fission rates to within 1% of reference solutions for two heterogeneous pressurized water reactor benchmarks.