狭缝式矩形喷动床中多粒度颗粒体系的最大喷动压降

在 15 0 mm× 5 0 mm× 110 0 mm的矩形喷动床中 ,研究了单一粒径体系和二组分及三组分混合粒径颗粒体系的最大喷动压降受颗粒粒径及粒度组成、静止床高和气体入口狭缝宽度的影响情况。实验采用宽度为2、4、6 mm三种宽度的狭缝式气体分布板 ,实验物料为单一粒径分别为 1、1.5、2 mm的玻璃珠。实验表明矩形喷动床的最大喷动压降与上述三种影响因素都有关系。本文还给出了最大喷动压降随这三种因素变化的实验关联式     

双喷嘴矩形喷动床中最小喷动速度的实验研究

在双喷嘴矩形喷动床内,以空气为喷动气体,研究了最小喷动速度的变化规律和影响因素。实验表明,双喷嘴矩形喷动床的最小喷动速度与颗粒粒径、床层高度及操作温度有关。并在综合考虑床层高度以及气体和固体颗粒的物性的基础上,得出了双喷嘴矩形喷动床最小喷动时雷诺数的经验关联式。     

导向管喷流床的最小喷动速度的研究

在内径９２ｍｍ的有机玻璃床内,使用四种没的物料,以空气作为喷动相流气体,综合考虑了床层的几何尺寸,以及气体和固体本身的物性,研究了导向管喷流床的最小喷动速度,得出了导向管喷流床的最小喷动速度的经验公式,以便对其设计和操作提供参考     

带导流管液固喷动床的最小喷动速度研究

在截面为矩形有机玻璃喷动床内，使用四种粒径的窄筛分球形玻璃珠，以常温水作为喷动和辅助液体。综合考虑床体的几何尺寸、操作参数以及液体和颗粒的物性特征，系统研究带导流管喷动床的最小喷动速度，得出最小喷动速度的经验公式，为设计和操作提供参考。     

大尺寸喷动床最低喷动速度的估算

最低喷动速度是喷动床设计的重要参数之一。过去人们习惯采用Mathur-Gisher公式来计算,但由于该公式是建立在小直径床层(D_c=0.076～0.3m)实验的基础上的,故在大直径床层上应用时,产生明显的偏差。本文通过实际数据分析,提出了大直径喷动床层最低喷动速度计算的经验公式。     

加压喷动床中细颗粒喷动特性

在内径分别为 186mm和 80mm的加压喷动床中 ,以空气为喷动介质 ,在 10 1～ 70 0kPa的压力范围内考察了几种不同粒度的细颗粒在加压下的喷动特性 .研究结果表明在不同的Re_t 内压力对最小喷动速度的影响不同 .实验还发现 ,随着压力的升高 ,喷动区直径增大 ,稳定操作区域增大 ,加压可明显改善喷动床的操作稳定性     

导向充气喷动床的临界充气速度

１前言在普通喷动床的环形区底部额外引入一股辅助气体,由于喷动气体和辅助气体各自独立地改变,气固系统将出现下列几种体系或操作状态：①固定床;②充气喷动床;③喷流床;④带射流的流化床。长期以来对充气喷动床与喷流床的区别不是很清楚的［１～５］。张怀清等［６...     

多气体入口的喷动床的喷动过程

本文叙述了一种适合于颗粒涂覆用的,具有特殊的多气体入口的喷动床。研究了这种喷动床在不同气流量和松装体积时的五种特征状态,给出了各种状态下的颗粒循环特点,并描述了在不同气流量和松装体积区间内出现不同喷动状态的相图。     

双喷嘴矩形喷动床流动性能实验研究

在120 mm×240 mm的双喷嘴矩形不锈钢床内,对新型双喷嘴矩形导流管喷动床的最小喷动速度和喷动高度进行了研究,考察了喷动气速、粒径、静床层高度、导流管直径、导流管安装位置对最小喷动速度和喷动高度的影响。结果表明:最小喷动速度随颗粒直径、导流管直径、导喷距的增大而增大,随静床层高度的增大而减小;喷动高度随喷动气速的增大而增大,随导流管直径的增大而减小,受静床层高度和导喷距的影响不大,并得出了最小喷动速度的关联式。     

Determination of Minimum Spouting Velocities in Conical Spouted Beds

Minimum spouting velocities in conical spouted beds have been obtained from pressure drops versus the superficial gas velocity curves, based on both increasing and decreasing the superficial gas velocity. It has been shown that the minimum spouting velocity from decreasing the superficial gas velocity is lower than from increasing the superficial gas velocity in most cases. This phenomenon is similar to that in conventional spouted beds and different from the early works. The experimental results also showed that there isn't significant difference in the pressure drop and U_ms under identical operating conditions between semi‐circular and circular conical spouted beds, and the same U_ms can be obtained from absolute pressure drops at any position above the gas inlet. The U_ms is found to increase with increasing the cone angle and static bed height, as well as the gas inlet diameter to a less extent.     

Minimum Spouting Velocity of Draft Tube Conical Spouted Beds Using the Neural Network Approach

A multilayer perceptron with back‐propagation learning algorithm is developed to predict the minimum spouting velocity (u_ms) in draft tube conical spouted beds. Six dimensionless variables involving ten essential geometric and operating parameters of the beds were taken as model inputs. To compare the model results with both experimental data and those predicted by the limited existing empirical equations, the root mean square error and the mean relative error are utilized. Although there is a complex relationship between the input variables and u_ms, and despite the huge number of data available, the steps of training and testing show good agreement with the corresponding experimental values. This demonstrates that an artificial neural network is a useful approach to predict u_ms, especially when the relationship between the geometric and operating parameters and u_ms is complex and difficult to define.     

Hydrodynamic Characteristics of a Powder‐Particle Spouted Bed with Powder Entrained in Spouting Gas

Spouting of 3.7 mm polyvinyl chloride particles in a cone‐based cylindrical column is subjected to entrainment of FCC powder in the spouting air. It is found that the powder entrainment reduces the minimum spouting velocity, increases the bed pressure drop and reduces the maximum spoutable bed height. At any given bed height and value of U/U_ms, there is a critical value of powder loading ratio above which spouting gives way to slugging.     

新颖环形喷动床颗粒喷动特性实验研究

一种新颖的环形喷动床由内外两个不同内径、同心的垂立圆筒组成,在环形空间底部设置多个喷口,在喷口两侧布置倾斜的导流板.研究颗粒在这种喷动床内的流动特性,探讨喷口结构、颗粒种类以及床内载料量对环形喷动床颗粒喷动特性的影响.实验结果表明:颗粒在环形喷动床内分为三个明显不同的区域,即颗粒填充移动区、密相喷动流化区以及稀相夹带区.当颗粒出现分区喷动后,随床内载料量的增多,填充移动区的高度维持不变,始终等于导流板的高度,而密相喷动区的高度不断增加.风量和颗粒种类对床层最大喷动量、密相喷动高度以及床层压力分布规律有着十分重要的影响.采用不同的喷口结构时,在相同的载料量下,直向喷口的密相喷动区高度更大,而且床内各测点的平均压力大于采用斜向喷口时的相应测点压力.     

Spouted bed hydrodynamics in a 0.91 m diameter vessel

Hydrodynamic measurements were obtained in a flat-based half-cylindrical column of diameter 0.91 m and inlet orifice diameters of 76 to 114 mm. Beds of 3.5 to 6.7 mm diameter particles with static depths of 0.53 to 1.83 m were spouted with air. In agreement with measurements by earlier workers in smaller columns, it was found necessary to operate with inlet orifice diameters less than about 30 times the mean particle diameter in order to be able to achieve stable spouting. Correlations for minimum spouting velocity developed on small vessels generally gave poor predictions for the large diameter vessel employed in this work and failed to predict the observed dependence of U_ms on the static bed height. Substantial dead regions where particles were stagnant were observed in the lower outer portion of the vessel. Other aspects of behaviour studied, including spout diameters and shapes, fountain heights, pressure profiles and gas velocities in the annulus, were qualitatively similar to those in smaller columns, although equations developed for the smaller vessels did not always provide accurate predictions.     

水平辅助气对喷动床流动特性影响的研究

在上部内径为 195mm柱状、下部为 6 0°锥体的喷动床中水平引入辅助气 ,考察了水平辅助气对流动特性的影响。实验结果发现 ,辅助气的水平引入比竖直或法向引入可以更有效地抑制喷动气体向环流区扩散 ,降低最小喷动气速。在总气速一定的条件下 ,增大辅助气速的比例 ,可以降低喷动区空隙率而使颗粒浓度增大 ,提高颗粒的循环流动量。相比而言 ,喷动气速对喷动区颗粒的流动速度影响较大 ,而水平辅助气速对环流区颗粒的流动速度影响较大     

Pressure Fluctuations in Jet Spouted Beds

Jet spouted beds that consisted of a transparent Plexiglas cylindrical column of 1 m high and a conical base with cone angles of 30°, 36°, and 40° were used in this study. The particles used were spherical glass beads with an average diameter of 1.7, 2.1 and 3 mm, respectively, and particle size of 2.2 – 3.1 mm, non‐spherical rice particles. The effect of size and shape of particles, and static bed height on the minimum jet spouting velocity, and standard deviation of pressure fluctuations, was investigated. The results show that the minimum jet spouting velocity and pressure drop increased as the bed height and particle size increased. The minimum jet spouting velocity could be determined from the plot of standard deviation of pressure fluctuations vs. superficial gas velocity. The results obtained were in close agreement with the results of other methods in the literature.     

Spouted bed and spout-fluid bed behaviour in a column of diameter 0.91 m

Hydrodynamic measurements were obtained in a half-column of diameter 0.91 m equipped with a conical base using particles of diameter 3.3 to 6.7mm with operation both as pure spouted beds and in the spout-fluid bed mode. Comparison of the experimental results for minimum spouting velocity with equations in the literature generally gave unsatisfactory agreement. On the other hand, the correlations of McNab (1972) and Had?isdmajlovi? et al. (1983) gave reasonable predictions of spout diameters in spouted and spout-fluid beds respectively. Hydrodynamic regimes with auxiliary air present were broadly similar to those determined in smaller columns. However, there were substantial dead regimes at the bottom of the column. A finite difference model based on the vector form of the Ergun equation gave good predictions of air flow distribution and longitudinal pressure profiles.     

Minimum spouting velocity in multiple spouted beds

Studies have been carried out in multiple spouted beds having 2, 3 and 4 spout cells; different fluid inlet orifices and different solids have been used with air and water as spouting fluids. The minimum spouting velocities are measured for different bed depths. The experimental data for particle Reynolds number at minimum spouting have been correlated and the square root mean deviation between the calculated and experimental values is found to be 8.75 %.