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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.
Michael Plagge, Ulrich Krause, Enrico Da Riva, Christoph Schäfer, Doris Forkel-Wirth
Nuclear Technology | Volume 198 | Number 1 | April 2017 | Pages 43-52
Technical Paper | doi.org/10.1080/00295450.2017.1291227
Articles are hosted by Taylor and Francis Online.
Being a particle physics laboratory, the European Organization for Nuclear Research (CERN) plans, constructs, and maintains installations emitting ionizing radiation during operation. Activation of present material is a consequence. Hence, fire scenarios for certain CERN installations must take into account the presence of radioactive material. Releases of gaseous, liquid, or solid combustion products, e.g., attached to aerosols, are taken so far into account by a worst case approach. Scenarios taking place in underground installations assume hence a smoke transport coefficient of 100% of release toward the surface level, independent of the local geometry. For a radioactive inventory identified in a certain fire load, this results in a conservative release.
To overcome this conservative worst case approach, a computational fluid dynamics model based on FM Global’s fireFoam 2.2.x is proposed. Its Lagrangian library was modified in order to provide aerosol release and deposition information based on more detailed interaction data between Lagrangian particles and their surrounding geometry. Results are shown for a CERN-typical large-scale experimental cavern placed 100 m below surface level. A simple diffusion burner is modeled inside the cavern to create a thermal plume emerging from a 1.5-MW fire over 14 min. Lagrangian particles are used to model aerosols with an aerodynamic diameter of 1, 10, and 100 μm, injected into the emerging thermal plume. Results for particle release and deposition vary according to aerodynamic diameter. In the present case, maximums of ~32% and 39% are found for 1- and 10-μm particles, respectively, being released to the surface level.