| dc.description.abstract | Porous media and randomly packed beds are used in a wide variety of engineering applications,
including thermal energy storage, modeling of the earth to be drilled in the petroleum industry, heap leaching for precious metal extraction in the mining industry, and many others. Another important application is as the core of a nuclear reactor. The very-high-temperature-reactor (VHTR) is a 4th generation, gas cooled, graphite-moderated nuclear reactor. One core geometry, the pebble-bed, utilizes a bed of randomly packed spherical fuel elements, which leads to complex flow and heat transfer behavior within the core. A deep understanding of the flow and heat transfer phenomena within the core is of high importance for safe design and operation of these next generation reactors. Many attempts to characterize the local flow and heat transfer phenomena in these geometries have been hindered by their complexity, so many studies have focused primarily on global parameters such as friction factor, total heat transfer, and the like. The combination of particle image velocimetry (PIV) and laser induced fluorescence (LIF) techniques and matched-index-of-refraction (MIR) facilities can allow for full field velocity and temperature measurements inside of these packed beds, along with other related geometries, i.e. a single sphere or cluster of spheres. These simplistic geometries share many complex flow phenomena with packed beds, such as impingement, high shear flows, and flow separations. Flow field data for each of these is taken, and a detailed uncertainty analysis is presented. Ensemble average velocities, root mean square (RMS) fluctuating velocities, and Reynolds shear stress are presented for each of these geometries, along with the convergence of these values. Various analysis techniques, such as spectral analysis, two-point cross-correlation (2PCC), proper orthogonal decomposition (POD), and vortex identification analysis are applied to the various data sets to extract deeper information about the captured physics. The data sets presented in each chapter can be used for code validation, and the increasing complexity of the geometry, along with the corresponding increase in complexity of flow physics can serve as building blocks toward validation of simulations for pebble bed geometries. | |
