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Experiments were carried out to observe the flow inside counterflow atomizers over a range of operating conditions and fluid properties. Liquids used were water and propylene glycol, while the gas was either air or helium. Liquid flow rates ranged from 10 ml/min to 40 ml/min, with gas liquid ratio (GLR) ranging from 0.1 to 0.6. The primary experiments used the 7-BM line of the Advanced Photon Source in Argonne National Laboratories with a 2.6 mm atomizer produced from (Poly)Ethyl-Ether-Ketone (PEEK). The X-Ray beam was operated in phase contrast mode, leading to interference patterns near the gas-liquid interface and enabling a qualitative understanding of the flow structure. Complementary optical work applied laser shadowgraphy to a 1 mm orifice atomizer constructed with quartz capillary tubing. A diffuse pulsed Nd:YAG laser backlight captured instantaneous gas-liquid interface positions in the internal flow. With both techniques, two distinct flow behaviors are observed corresponding to low and high GLR values. At low GLR, the inertia of the injected gas is insufficient to penetrate the liquid downflow. The gas stream entering the mixing chamber in the upstream direction is immediately deflected by the denser liquid and enters the discharge tube around a central liquid jet, which ismore »Free, publicly-accessible full text available May 25, 2023
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This study explores how to exploit a compute cache architecture to bring computation close to memory. Using a combination of experimental prototypes, benchmarking, and modeling & simulation, we perform architectural and application explorations of emerging/notional memory devices and compute cache architectures of the future to accelerate data analytics applications.
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This study explores how to exploit a compute cache architecture to bring computation close to memory. Using a combination of experimental prototypes, benchmarking, and modeling & simulation, we perform architectural and application explorations of emerging/notional memory devices and compute cache architectures of the future to accelerate data analytics applications.