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Computational study of bubble coalescence/break-up behaviors and bubble size distribution in a 3-D pressurized bubbling gas-solid fluidized bed of Geldart A particles
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作者 Teng Wang Zihong Xia Caixia Chen 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2022年第4期485-496,共12页
A computational study was carried out on bubble dynamic behaviors and bubble size distributions in a pressurized lab-scale gas-solid fluidized bed of Geldart A particles.High-resolution 3-D numerical simulations were ... A computational study was carried out on bubble dynamic behaviors and bubble size distributions in a pressurized lab-scale gas-solid fluidized bed of Geldart A particles.High-resolution 3-D numerical simulations were performed using the two-fluid model based on the kinetic theory of granular flow.A finegrid,which is in the range of 3–4 particle diameters,was utilized in order to capture bubble structures explicitly without breaking down the continuum assumption for the solid phase.A novel bubble tracking scheme was developed in combination with a 3-D detection and tracking algorithm(MS3 DATA)and applied to detect the bubble statistics,such as bubble size,location in each time frame and relative position between two adjacent time frames,from numerical simulations.The spatial coordinates and corresponding void fraction data were sampled at 100 Hz for data analyzing.The bubble coalescence/break-up frequencies and the daughter bubble size distribution were evaluated by using the new bubble tracking algorithm.The results showed that the bubble size distributed non-uniformly over cross-sections in the bed.The equilibrium bubble diameter due to bubble break-up and coalescence dynamics can be obtained,and the bubble rise velocity follows Davidson’s correlation closely.Good agreements were obtained between the computed results and that predicted by using the bubble break-up model proposed in our previous work.The computational bubble tracking method showed the potential of analyzing bubble motions and the coalescence and break-up characteristics based on time series data sets of void fraction maps obtained numerically and experimentally. 展开更多
关键词 Pressurized gas-solid bubbling fluidized bed geldart a particles Bubble size distribution COaLESCENCE BREaK-UP Bubble tracking algorithm
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Two-fluid modeling of Geldart A particles in gas-fluidized beds 被引量:16
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作者 M.A. van der Hoef J.A.M. Kuipers 《Particuology》 SCIE EI CAS CSCD 2008年第6期540-548,共9页
We have investigated the effect of cohesion and drag models on the bed hydrodynamics of Geldart A particles based on the two-fluid (TF) model. For a high gas velocity U0 = 0.03 m/s, we found a transition from the ho... We have investigated the effect of cohesion and drag models on the bed hydrodynamics of Geldart A particles based on the two-fluid (TF) model. For a high gas velocity U0 = 0.03 m/s, we found a transition from the homogeneous fluidization to bubbling fluidization with an increase of the coefficient C1, which is used to account for the contribution of cohesion to the excess compressibility. Thus cohesion can play a role in the bed expansion of Geldart A particles. Apart from cohesion, we have also investigated the influence of the drag models. When using the Wen and Yu drag correlation with an exponent n = 4.65, we find an under-prediction of the bed expansion at low gas velocities (U0 = 0.009 m/s). When using a larger exponent (n = 9.6), as reported in experimental studies of gas-fluidization, a much better agreement with the experimental bed expansion is obtained. These findings suggest that at low gas velocity, a scale-down of the commonly used drag model is required. On the other hand, a scale-up of the commonly used drag model is necessary at high gas velocity (U0 = 0.2 and 0.06 m/s). We therefore conclude that scaling the drag force represent only an ad hoc way of repairing the deficiencies of the TF model, and that a far more detailed study is required into the origin of the failure of the TF model for simulating fluidized beds of fine powders. 展开更多
关键词 Gas-fluidized bed geldart a particles Two-fluid model Cohesive force Drag correlation
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