Sintering involves consolidation of powders under the application of heat to form solids of highe... more Sintering involves consolidation of powders under the application of heat to form solids of higher density and is often the final step in the processing of ceramic materials. The time-temperature cycles used in sintering affect the kinetics and, in turn, influence the quality of the sintered product. Considering the densification mechanisms controlled by grain boundary diffusion along with interface reaction and the grain growth mechanism, this paper presents a systematic numerical study on the sintering of nanocrystalline yttria tetragonal stabilised zirconia and microscaled a-alumina, to bring out the effects of the time-temperature cycles on their sintering behaviour. Effects of initial grain size are also examined. Based on the studies, empirical correlations are developed that relate the final grain size and the sintering time to the temperature cycle. The results serve as guidelines in the design of time-temperature cycles for the sintering of the two material systems considered. A d pre-exponential parameter controlling densification, s 21 A g pre-exponential parameter controlling grain growth, m s 21 L grain size, m : L grain growth rate, m s 21 L 0 initial grain size, m : L 0 grain growth rate parameter, m s 21 : L 00 material property controlling grain growth, m mol J 21 s 21 Q d activation energy for densification, J mol 21 Q g activation energy for grain growth, J mol 21 R universal gas constant, J mol 21 K 21 t time, s t s sintering time, s T absolute temperature, K T c critical temperature, K T l room temperature, K T m intermediate hold temperature, K T h maximum temperature in the cycle, K a o constant in empirical correlation for grain size b o constant in empirical correlation for sinter-ing time c s surface free energy, J m 22 : e v volumetric strain rate, s 21 : e 0 uniaxial strain rate, s 21 : e 00 material property controlling densification, mol J 21 s 21 r fractional density r 0 initial fractional density : r b densification rate due to grain boundary diffusion, s 21 : r r densification rate due to interface reaction, s 21 r T theoretical density, kg m 23 s e effective stress, N m 22 s m mean stress, N m 22 s 0 uniaxial stress, N m 22 s s sintering potential, N m 22
Fluidized beds with multiple jets have widespread industrial applications. They are used to aid i... more Fluidized beds with multiple jets have widespread industrial applications. They are used to aid in proper mixing of coal or biomass in the bed, which in turn increases the combustion and heat transfer. The objective of this paper is to investigate the jet interactions and hydrodynamics of a fluidized bed with multiple jets. Discrete Element Modeling coupled with a CFD code GenIDLEST has been used to numerically simulate 9 jets. The results are compared with published experiments. Mono dispersed particles of size 550 microns are used with 1.4 times the minimum fluidization for the particles. Two dimensional computations have been performed. The solid fraction at different heights from the jetting bed is compared with the experiments along with the solid circulation at the grid zone or the jetting zone. Average solid fraction across the cross-section of the bed is plotted along the height and compared with the experiments to estimate the bed expansion due to fluidization. Comparison of time averaged jet heights with the experiments is also shown. Discrepancies between the experiments and simulations are discussed in the context of the dimensionality of the simulations. The time averaged solid fraction at different heights from the distributor plate match well with the experimental results except near the walls. A slight over prediction of solid fraction values is obtained near the walls from the simulations. The average solid fraction along the height of the bed is in good agreement with the experiments, showing similar trends in bed expansion for both the experiments and simulations. The results obtained from DEM computations serve as validation for the experiments and help us understand the complex jet interaction and solid circulation patterns in a multiple jet fluidized bed system.
Sintering involves consolidation of powders under the application of heat to form solids of highe... more Sintering involves consolidation of powders under the application of heat to form solids of higher density and is often the final step in the processing of ceramic materials. The time-temperature cycles used in sintering affect the kinetics and, in turn, influence the quality of the sintered product. Considering the densification mechanisms controlled by grain boundary diffusion along with interface reaction and the grain growth mechanism, this paper presents a systematic numerical study on the sintering of nanocrystalline yttria tetragonal stabilised zirconia and microscaled a-alumina, to bring out the effects of the time-temperature cycles on their sintering behaviour. Effects of initial grain size are also examined. Based on the studies, empirical correlations are developed that relate the final grain size and the sintering time to the temperature cycle. The results serve as guidelines in the design of time-temperature cycles for the sintering of the two material systems considered. A d pre-exponential parameter controlling densification, s 21 A g pre-exponential parameter controlling grain growth, m s 21 L grain size, m : L grain growth rate, m s 21 L 0 initial grain size, m : L 0 grain growth rate parameter, m s 21 : L 00 material property controlling grain growth, m mol J 21 s 21 Q d activation energy for densification, J mol 21 Q g activation energy for grain growth, J mol 21 R universal gas constant, J mol 21 K 21 t time, s t s sintering time, s T absolute temperature, K T c critical temperature, K T l room temperature, K T m intermediate hold temperature, K T h maximum temperature in the cycle, K a o constant in empirical correlation for grain size b o constant in empirical correlation for sinter-ing time c s surface free energy, J m 22 : e v volumetric strain rate, s 21 : e 0 uniaxial strain rate, s 21 : e 00 material property controlling densification, mol J 21 s 21 r fractional density r 0 initial fractional density : r b densification rate due to grain boundary diffusion, s 21 : r r densification rate due to interface reaction, s 21 r T theoretical density, kg m 23 s e effective stress, N m 22 s m mean stress, N m 22 s 0 uniaxial stress, N m 22 s s sintering potential, N m 22
Fluidized beds with multiple jets have widespread industrial applications. They are used to aid i... more Fluidized beds with multiple jets have widespread industrial applications. They are used to aid in proper mixing of coal or biomass in the bed, which in turn increases the combustion and heat transfer. The objective of this paper is to investigate the jet interactions and hydrodynamics of a fluidized bed with multiple jets. Discrete Element Modeling coupled with a CFD code GenIDLEST has been used to numerically simulate 9 jets. The results are compared with published experiments. Mono dispersed particles of size 550 microns are used with 1.4 times the minimum fluidization for the particles. Two dimensional computations have been performed. The solid fraction at different heights from the jetting bed is compared with the experiments along with the solid circulation at the grid zone or the jetting zone. Average solid fraction across the cross-section of the bed is plotted along the height and compared with the experiments to estimate the bed expansion due to fluidization. Comparison of time averaged jet heights with the experiments is also shown. Discrepancies between the experiments and simulations are discussed in the context of the dimensionality of the simulations. The time averaged solid fraction at different heights from the distributor plate match well with the experimental results except near the walls. A slight over prediction of solid fraction values is obtained near the walls from the simulations. The average solid fraction along the height of the bed is in good agreement with the experiments, showing similar trends in bed expansion for both the experiments and simulations. The results obtained from DEM computations serve as validation for the experiments and help us understand the complex jet interaction and solid circulation patterns in a multiple jet fluidized bed system.
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