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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.
Yong Soo Kim, Chang Hwan Park, Byoung Uhn Bae, Goon Cherl Park, Kune Yull Suh, Un Chul Lee
Nuclear Technology | Volume 149 | Number 2 | February 2005 | Pages 200-216
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT05-A3590
Articles are hosted by Taylor and Francis Online.
This study concerns the development of an integrated calculation methodology with which to continually and consistently analyze the progression of an accident from the design-basis accident phase via core uncovery to the severe accident phase. The depletion rate of reactor coolant inventory was experimentally investigated after the safety injection failure during a large-break loss-of-coolant accident utilizing the Seoul National University Integral Test Facility (SNUF), which is scaled down to 1/6.4 in length and 1/178 in area from the APR1400 [Advanced Power Reactor 1400 MW(electric)]. The experimental results showed that the core coolant inventory decreased five times faster before than after the extinction of sweepout in the reactor downcomer, which is induced by the incoming steam from the intact cold legs. The sweepout occurred on top of the spillover from the downcomer region and expedited depletion of the core coolant inventory. The test result was simulated with the MAAP4 severe accident analysis code. The calculation results of the original MAAP4 deviated from the test data in terms of coolant inventory distribution in the test vessel. After the calculation algorithm of coolant level distribution was improved by including the subroutine of pseudo pressure buildup, which accounts for the differential pressure between the core and downcomer in MAAP4, the core melt progression was delayed by hundreds of seconds, and the code prediction was in reasonable agreement with the overall behavior of the SNUF experiment.