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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.
Arif Nesimi Kiliç
Nuclear Technology | Volume 108 | Number 3 | December 1994 | Pages 413-420
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT94-A35023
Articles are hosted by Taylor and Francis Online.
A simple approximation for predicting the concrete erosion rate and depth is derived based on the heat balance integral method for conduction with the time-dependent boundary conditions. The problem is considered a four-region model including separate, moving heat sinks at the boundaries due to endothermic decomposition reactions. Polynomial temperature profiles are assumed, and the results are compared with previous experimental data and other analytical solutions. Since the technique provides an approximate temperature distribution on the average, it does not give the real temperature evaluation but provides a simple prediction of the erosion rates and the depth of defaulted concrete in terms of the parameters that are important during the physical phenomena. Because of its simplicity and reliability, the model might be useful for the larger molten core/concrete interaction codes and aerosol generation models.