In trickle bed reactor (TBR), the gas-liquid mass transfer is closely related to the thickness of liquid film and the wetting of catalyst particles. Therefore, knowledge on the flow and distribution of liquid film on particle surface is critical for evaluating the performance of TBR. In this work, high-speed camera was used to study the flow behavior of liquid film by using continuous droplets impacting on the top of particles with several layers. It was found that liquid tends to accumulating toward the contact point between adjacent particles due to capillary force. When the liquid inlet flow rate doubles, the wetting ratio of the particle surface increases by about 30%, while the liquid film thickness doubles. With the particle surface wettability increasing, the wetting ratio of particle surface can be improved while the liquid film thickness remains almost unchanged.

This work proposes an ensemble learning-based catalytic cracking coke yield prediction model called the harmonic-ensembled extreme learning machine (HEELM). The model integrates extreme learning machine (ELM) base learners with different activation functions to improve the overall prediction effect. An overfitting index is proposed, and the optimal number of hidden layer nodes of ELM-base learners is determined with it. By examining the influence of different activation functions on the prediction results, the best activation function structure of the ELM-base learner has been determined. Besides, a harmonic layer is established to determine the weight of each base learner in real-time. The proposed model is validated using 1.5 years of historical data from China's commercial fluidized catalytic cracking (FCC) plant. The results show that the proposed model has outperformed most other ELM-base learners. The relative prediction error is further reduced by 10.97% after introducing the harmonic layer. The proposed model exhibits stable performance with good generalization in three segments of industrial data, and it has guiding significance for stable operation and CO2 emission reduction of the FCC plant.

采用CFD方法对安置盘环挡板的汽提器进行了模拟计算,对比了盘环挡板上有无开孔情况下的颗粒流动分布。结果表明,在盘环挡板上进行开孔可有效减少“气垫”区域,使气体与颗粒更顺利地穿透挡板进行高效接触。此外,通过对比不同开孔形式下

Y Gas-liquid reactors containing bubbles are intensively used in the chemical industry. However, the gas-liquid mass transfer is usually the rate-limiting step. One possible way to intensify the mass transfer is the application of sub-millimeter bubbles (1-1000 lm) which efficiently increase interfacial area. Literature usually focused on bubbles larger than 1000 lm, and it still needs to be studied whether the frequently-used literature equations for terminal rise velocity and mass transfer can accurately predict the behavior of sub-millimeter bubbles. Therefore, the terminal rise velocity and mass transfer rate of single sub-millimeter bubbles were obtained by numerical simulation. It was found that the literature equations could not accurately predict the behavior of sub-millimeter bubbles over the whole size range. New equations were proposed to improve calculation accuracy, with which the terminal rise velocity and mass transfer rate of sub-millimeter bubbles can be accurately predicted. (C) 2021 Elsevier Ltd. All rights reserved.

The gas-solids flow in high-density downers with FCC particles was simulated by Computational Particle Fluid Dynamics (CPFD) approach. A drag model was proposed based on the equivalent diameter of cluster with the analysis of force balance on particle cluster. A global sensitivity analysis method was used to analyze the influencing factors of cluster size. The drag model was incorporated into the three-dimensional (3D) CPFD approach to simulate the gas-solids flow in two different downers operating at various conditions. 3D CPFD simulation provided detailed trajectories and distributions of solids. Good agreements of the predicted solids holdup and velocity with experimental data were achieved at both low and high-density conditions, which verified the rationality and applicability of the present drag model considering the characteristics of particle cluster in the downer. Finally, the flow and clustering behavior in the high-density downer were adequately analyzed and compared with that in low-density downer. (C) 2020 Elsevier B.V. All rights reserved.

采用计算流体力学（CFD）方法对挡板鼓泡床内气-固流动进行模拟计算,基于模拟结果建立了识别和分析气泡特性的方法,分析有、无挡板的鼓泡床中气泡运动特性的差异,揭示挡板对鼓泡床内气泡的作用机制。研究结果表明,挡板的存在可以强化气泡破碎作用,大气泡经过挡板时,破碎成多个小气泡。挡板只在一定区域内对气泡存在作用,如需在整个床层内调控气泡行为,需设置多层挡板。在挡板的作用区域内,气泡平均尺寸明显减小、气泡数量增多。在较低气速下,挡板对鼓泡床内气泡的影响较小;随着气速的提高,挡板对气泡的作用逐渐加强,气-固接触更加均匀。

The difference of gas-solids flow between a circulating fluidized bed (CFB) downer and riser was compared by computational particle fluid dynamics (CPFD) approach. The comparison was conducted under the same operating conditions. Simulation results demonstrated that the downer showed much more uniform solids holdup and solids velocity distribution compared with the riser. The radial non-uniformity index of the solids holdup in the riser was over 10 times than that in the downer. In addition, small clusters tended to be present in the whole downer, large clusters tended to be present near the wall in riser. It was found that the different cluster behavior is important in determining the different flow behaviors of solids in the downer and riser. While the particle residence time increased evenly along the downward direction in the downer, particles with both shorter and longer residence time were predicted in the whole riser. The nearly vertical cumulative residence time distribution (RTD) curve in the downer further demonstrated that the solids back-mixing in the downer is limited while that in the riser is severe. Solids turbulence in the downer was much weaker compared with the riser, while the large clusters formation near the wall in the riser would hinder solids transportation ability.