Previous research findings and experiential accounts have provided evidence that specific compone... more Previous research findings and experiential accounts have provided evidence that specific components of coal ash play a catalytic role in the dry desulfurization of flue gas such that their contributions need to be considered for determining the optimal amount of desulfurizing agent such as limestone. The purpose of this study was to quantify the desulfurization characteristics of coal ash in a 500 MW pulverized coal combustion (PC) boiler as well as a 1000 MW circulating fluidized bed combustion (CFBC) boiler. In parallel with a year-long data collection of coal blends and emission characteristics, a series of temperature-controlled fixed bed (lab scale) experiments were conducted for 11 individual (but representative) coal samples. The results indicated that desulfurization by fly ashes appeared to proceed roughly in proportion to the total alkali (TA) contents of the ash, which were consistent with our preliminary test result of the CFBC boiler. In the PC boiler, however, the desulfurization reaction seemed to be very kinetically limited, apparently deactivating the TA components. We developed a practical equation for a priori prediction of SO 2 concentration based on the sulfur content of coal blends.
Size-independent unipolar charging of nanoparticles at high concentrations using vapor condensati... more Size-independent unipolar charging of nanoparticles at high concentrations using vapor condensation and its application for improving DMA size-selection efficiency,
International Journal of Heat and Mass Transfer, 2019
A particle-reinforced composite material is a matrix with thermally conductive particles that has... more A particle-reinforced composite material is a matrix with thermally conductive particles that has a diverse range of applications from electronics to energy harvesting/storage systems. In the engineering design of a particle-reinforced composite material for application, it is crucial to accurately and practically predict its effective thermal conductivity. Here, we report the development of a simple analytical model for predictions with improved accuracy and applicability. Comprehensive evaluation of existing models was first conducted to clarify their limitations in prediction accuracy and applicability to various experimental conditions. To overcome the challenges of the existing models, our new model was derived to consider the effect of shape, particle aggregation, and mutual interaction of particles on effective thermal conductivity. Lattice Boltzmann simulations were conducted to obtain a quasi-universal coefficient representing interactions of particles, whereas a shape coefficient characterizing microstructures of aggregated particles was obtained from experimental data available from literature. As a result, our model prediction outperformed the existing models in its prediction accuracy, and it could be applicable to any experimental circumstances where previous model predictions are inappropriate to use.
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Papers by Jeonggeon Kim