As part of the US Department of Energy (DOE) National Nuclear Security Administration’s (NNSA) initiative to reduce the enrichment of research and test reactors, this research project sets out to investigate the conversion of HFIR from a high enriched uranium (HEU) core to a low enriched uranium (LEU) core.
High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is a source of thermal and cold neutrons for research projects throughout the US used to study phenomena in numerous scientific and engineering disciplines. As part of the US Department of Energy (DOE) National Nuclear Security Administration’s (NNSA) initiative to reduce the enrichment of research and test reactors, a research project is underway to investigate the conversion of HFIR from a high enriched uranium (HEU) core to a low enriched uranium (LEU) core. Due to the complex channel geometry and the difficulty of performing LEU testing and experiments, data supporting this conversion is highly limited. Therefore, high-fidelity numerical data is required to verify and calibrate Reynolds-Averaged Navier-Stokes models.
Direct numerical simulation (DNS) of turbulent single- and two-phase flows at a leadership computing facility allows for users to attain unprecedented level of detail and can answer fundamental questions about the interaction and evolution of turbulence within complex geometries. The highly detailed simulation of all turbulent structures using a DNS approach will allow for the collection of statistical information relevant to turbulent flow parameters, such as the turbulent kinetic energy, k-ε model constants and the Prandtl number required to enforce the correct wall heat transfer.
Two subprojects will generate single-phase flow results for geometries relevant to HFIR, including (i) complex turbulent flow through the full radial span of a HFIR coolant channel and (ii) the simulation of turbulent flow through involute plates representing a portion of the HFIR coolant channel. The research code PHASTA will be utilized to study complex physical phenomena in unprecedented detail and allow for the collection of numerical data based on first-principal calculations. Major statistical parameters, such as the mean velocity profile, turbulent kinetic energy and secondary flow structure formation will be assessed to develop a new and more sophisticated understanding about single-phase flows in an involute geometry.
With the assistance of leadership computing facilities, detailed numerical data will be produced for the development of new closure laws to improve the prediction accuracy of computational fluid dynamics (CFD) models. These developments will help to capture turbulent flows in fine detail and facilitate the thermal-hydraulic design of HFIR and next generation energy systems.