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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.
Yiban Xu, Robert A. Brewster, Michael E. Conner, Zeses E. Karoutas, L. David Smith, III
Nuclear Technology | Volume 205 | Number 1 | January-February 2019 | Pages 57-67
Technical Paper | doi.org/10.1080/00295450.2018.1510265
Articles are hosted by Taylor and Francis Online.
Critical heat flux (CHF) is a primary parameter for nuclear fuel design and plant operation safety. CHF values are normally obtained from fuel bundle integral departure from nucleate boiling (DNB) or dryout experiments. These experiments are expensive, and detailed measurements (bubble dynamics, void fraction distribution, etc.) are difficult to obtain, particularly under typical pressurized water reactor (PWR) conditions of high pressure and temperature. Therefore, it is highly desirable that computational tools such as computational fluid dynamics (CFD) provide detailed flow and heat transfer information that will efficiently facilitate design improvements of PWR fuel designs.
For the CFD studies described in this paper, an Eulerian-Eulerian two-phase modeling approach was adopted to predict DNB in a fuel assembly with mixing vane grids. Subcooled flow boiling was simulated using heat flux partition modeling and phase interactions. Direct addition of heat to the vapor was activated when the local vapor volume fraction reached a specified critical value. Emphases were placed on bubble departure diameter, phase interactions, and pressure drop for two-phase modeling development. Simulations were conducted in steady state. Solution convergence was closely monitored for physical variables in terms of local and global scales. A multi-indicator approach was used to judge DNB occurrence, and a new integrated DNB indicator is proposed.
For validation, this CFD-based DNB modeling methodology was applied to two 5 × 5 rod bundle tests equipped with mixing vane grids and uniform axial power shape. The tests were performed under PWR conditions (16.5 MPa) and produced an exit quality of −4% and 11%. The CFD results show the validity of the new DNB indicator and the improved reliability with the multi-indicator approach. Correctly predicted DNB occurrence locations show the promise of the current modeling approach. Utilization of measured pressure drop and fluid temperature data may permit some bottom-up validations, and this effort may prompt further improvements for experimental measurements, particularly under high-pressure conditions.