PARTICLE IMAGE VELOCIMETRY BASED FLOW CHARACTERIZATION IN A RANDOMLY PACKED PEBBLE BED CORE GEOMETRY

Abstract

Packed spherical pebble beds have widespread uses used due to their applications in a wide variety of engineering applications. Pebble Bed Reactors (PBR) are a Generation-IV nuclear reactor design which are a subject of extensive research, utilizing packed spherical bed arrangements. These packed beds have an intricate yet randomized geometry with vacant spaces, increasing the flow complexity in PBR cores which require detailed characterizations. The presented experimental research on a facility of randomly packed pebble bed spheres investigates the complex flow phenomena to evaluate fluid dynamics within a PBR core. By utilizing Particle Image Velocimetry (PIV) among the spheres, high-fidelity velocity measurements and Laser Induced Fluorescence (LIF) were carried out. In this facility, Matched Index of Refraction (MIR) method provides a clear non-intrusive view of the sphere void regions to analyze the flow with precise resolution. In order to provide a comprehensive profile of the flow and geometry that was studied, a three-dimensional reconstruction of the flow was carried out. This serves the primary purpose of providing the geometry for validation of simulation as well as the secondary purpose of illustrating the geometry of the packed bed. The flow was investigated for various Reynolds numbers (𝑅𝑅𝑅𝑅) to provide a comprehensive profile of the flow. The experiments investigated isothermal and non-isothermal conditions to examine the differences in flow dynamic patterns within packed spheres. The results characterize first- and second-order flow statistics including velocity magnitude, mean velocity components, velocity fluctuation components, Reynolds stresses, vorticity, turbulence kinetic energy, Flow Reconstruction, Proper Orthogonal Decomposition, Spatial Proper Orthogonal Decomposition, and Multi-Scale Proper Orthogonal Decomposition. Two-point spatial cross-correlation analysis provided the spatial extents of the turbulence patterns in the PIV measurement window. The persistence power spectral density analysis detailed the dominant frequencies of the velocity fluctuation components contributing toward turbulent flow behavior. The vortex identification analysis revealed the instances of localized and traveling flow structures in the investigated pebble bed arrangement. Finally, LIF results offer a revealing examination of temperature distribution across three distinct Reynolds numbers, presenting a nuanced understanding of thermal dynamics within the flow. The experimental results provide unique high-fidelity data sets for computational fluid dynamics model development and validation – important for the design and developmental optimization of PBR core geometries.