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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.
P. Balestra, C. Parisi, A. Alfonsi, C. Rabiti
Nuclear Technology | Volume 193 | Number 1 | January 2016 | Pages 175-182
Technical Paper | Special Issue on the RELAP5-3D Computer Code | doi.org/10.13182/NT14-138
Articles are hosted by Taylor and Francis Online.
ENEA “Casaccia” Research Center is collaborating with Idaho National Laboratory performing activities devoted to the validation of the Parallel and Highly Innovative Simulation for INL Code System (PHISICS) neutron simulation code. In such framework, the AER-DYN-002 and AER-DYN-003 control rod (CR) ejection benchmarks were used to validate the coupled codes RELAP5-3D/PHISICS.
The AER-DYN-002 benchmark provides a test case of a CR ejection accident in a VVER-440 at hot-zero-power and end-of-cycle conditions assuming an adiabatic fuel and taking into account only the fuel temperature feedback. The AER-DYN-003 benchmark is based on the same problem; however, the moderator density feedback and the coolant heat removal are also considered. A RELAP5-3D core channel-by-channel, thermal-hydraulic nodalization was developed and coupled, first with the RELAP5-3D internal neutronic routine NESTLE and then with the PHISICS code. Analysis of the AER-DYN-002 results shows that the steady-state solutions are in good agreement with the other participants’ average solution, while some differences are shown in the transient simulations. In the AER-DYN-003 benchmark, however, both steady-state and transient results are in good agreement with the average solution.