Computational study of full-scale VHTR lower plenum for turbulent mixing assessment Academic Article uri icon

abstract

  • © 2019 Elsevier Ltd Next-generation nuclear reactors are poised to efficiently provide reliable power at enhanced safety levels for many years to come. Among the fundamental designs for these reactors is the very-high-temperature reactor (VHTR), which employs helium as the primary coolant and has the potential of reaching elevated temperatures such that chemical processing (e.g., electrolysis for hydrogen production) is viable alongside traditional electricity generation. This and other next-generation reactors also represent a strategic bridge for ultimately transitioning from fossil fuel-dominated energy portfolios to one where renewable options abound. For the VHTR, the ultimate goal of constructing a new plant will be preceded by additional fundamental research aimed at generating trusted models for behavior prediction under normal and accident scenarios. This paper presents a detailed computational fluid dynamics simulation of the lower plenum, where hot coolant from the core mixes together in a turbulent fashion before traveling to power conversion equipment. Because the flow is expected to enter the lower plenum across a wide range of temperatures and velocities, concerns exist when the mixing is incomplete. The potential hot spots on cylindrical support pedestals and the uniformity of the main outlet are the primary metrics of interest in this study, along with flow velocities and temperatures at different locations within the lower plenum. Three locations are probed in detail and suggest a large range exists for approach velocities and temperatures. A large degree of stratification is also seen on the surfaces of the support pedestals, suggesting a facility should accommodate testing for such behavior. The characterizations presented provide the valuable data needed in order to design appropriate experimental testbeds, where scaled modeling can be carried out in a manner meaningful in predicting the full-scale behavior.

author list (cited authors)

  • Clifford, C. E., Fradeneck, A. D., Oler, A. M., Salkhordeh, S., & Kimber, M. L.

citation count

  • 2
  • 3

publication date

  • December 2019