Experimental investigation on the gravity driven discharge of cohesive particles from a silo with two outlets

An experimental study on the gravity driven discharge of cohesive particles from a silo with two outlets was performed.The discharge behaviors under the conditions that a single outlet was open and two outlets were open were investigated by varying the moisture content of the particles and the filling height of the particles in the silo.The results show that the discharge rate of the cohesive particles increases gradually at the beginning,then almost keeps constant,and finally drops obviously.The discharge rate in case of two openings is around 1.1–1.6 times that in case of a single opening.Larger filling height leads to lower discharge rate in case of a single opening but results in higher discharge rate in case of two openings.Furthermore,the avalanche dynamics in case of a single opening was examined,and the mixing behavior of the cohesive particles was evaluated.It is observed that the discharge flow is promoted by the avalanche phenomenon in the silo,generating a general trend that the normalized mass of discharge increases with the filling height at higher moisture contents.In case of a single opening,the transition from mass flow to funnel flow favors the particle mixing,resulting in an increasing mixing index as the moisture content increases.In general,a better performance of mixing can be achieved in case of a single opening compared with in case of two openings.This study provides vital information for fundamental understanding of the gravity driven discharge of cohesive particles from the silo with multiple outlets.

Analysis of cohesive particles mixing behavior in a twin-paddle blender:DEM and machine learning applications

This research paper presents a comprehensive discrete element method(DEM)examination of the mixing behaviors exhibited by cohesive particles within a twin-paddle blender.A comparative analysis between the simulation and experimental results revealed a relative error of 3.47%,demonstrating a strong agreement between the results from the experimental tests and the DEM simulation.The main focus centers on systematically exploring how operational parameters,such as impeller rotational speed,blender's fill level,and particle mass ratio,influence the process.The investigation also illustrates the significant influence of the mixing time on the mixing quality.To gain a deeper understanding of the DEM simulation findings,an analytical tool called multivariate polynomial regression in machine learning is employed.This method uncovers significant connections between the DEM results and the operational parameters,providing a more comprehensive insight into their interrelationships.The multivariate polynomial regression model exhibited robust predictive performance,with a mean absolute percentage error of less than 3%for both the training and validation sets,indicating a slight deviation from actual values.The model's precision was confirmed by low mean absolute error values of 0.0144(80%of the dataset in the training set)and 0.0183(20%of the dataset in the validation set).The study offers valuable insights into granular mixing behaviors,with implications for enhancing the efficiency and predictability of the mixing processes in various industrial applications.

Enhancing mixing of cohesive particles by baffles in a rotary drum

A soft-sphere discrete cohesive powder model was used to simulate the transverse mixing of particles in a rotary drum. Using this model, the effect of cohesion strength and baffle length was investigated. Mixing time （tR） and mixing entropy were used to characterize the mixing behavior. The results showed that increasing particle cohesiveness increases tR. Baffles enhanced transverse mixing, especially for high- cohesive particles. Moreover, the baffle length played a significant role on mixing. An optimized length of 0.50 （L/R） enhances transverse mixing for high-cohesive particles, Further increases in baffle length only decreases the mixing rate by impeding the surface flow layer. In contrast to high-cohesive particles, low-cohesive particles needed much shorter baffles.A soft-sphere discrete cohesive powder model was used to simulate the transverse mixing of particles in a rotary drum. Using this model, the effect of cohesion strength and baffle length was investigated. Mixing time （tR） and mixing entropy were used to characterize the mixing behavior. The results showed that increasing particle cohesiveness increases tR. Baffles enhanced transverse mixing, especially for high- cohesive particles. Moreover, the baffle length played a significant role on mixing. An optimized length of 0.50 （L/R） enhances transverse mixing for high-cohesive particles. Further increases in baffle length only decreases the mixing rate by impeding the surface flow layer. In contrast to high-cohesive particles, low-cohesive particles needed much shorter baffles.

Bubbling behavior of cohesive particles in a two-dimensional fluidized bed with immersed tubes

Fluidization hydrodynamics are greatly influenced by inter-particle cohesive forces. This paper studies the fluidization of large cohesive particles in a two-dimensional fluidized bed with immersed tubes using “polymer coating” to introduce cohesive force, to gain better understanding of bubbling behavior when particles become cohesive and its effect on chemical processes. The results show that the cohesive force promotes bubble splitting in the tube bank region, thereby causing an increase in the number and a decline in the aspect ratio of the bubbles. As the cohesive force increases within a low level, the bubble number increases and the bubble diameter decreases, while the aspect ratio exhibits different trends at different fluidization gas velocities. The difference in the evolution of bubble size under various cohesive forces mainly takes place in the region without tubes. When the cohesive force is large enough to generate stable agglomerates on the side walls of the bed, the bubble number and the bed expansion sharply decrease. The tubes serve as a framework that promotes the agglomeration, thus accelerating defluidization. Finally, the bubble profile around tubes was studied and found to greatly depend both on the cohesive forces and the location of tubes.

Multi-fluid Eulerian simulation of mixing of binary particles in a gas-solid fluidized bed with a cohesive particle-particle drag model

A particle-particle(p-p)drag model is extended to cohesive particle flow by introducing solid surface energy to characterize cohesive collision energy loss.The effects of the proportion of cohesive particles on the mixing of binary particles were numerically investigated with the use of a Eulerian multiphase flow model incorporating the p-p drag model.The bed expansion,mixing,and segregation of Geldart-A and C particles were simulated with varying superficial velocities and Geldart-C particle proportions,from which we found that the p-p drag model can reasonably predict bed expansion of binary particles.Two segregation types of jetsam-mixture-flotsam and mixture-flotsam processes were observed during the fluidization processes for the Geldart-A and C binary particle system.The mixing processes of the binary particle system can be divided into three scales:macro-scale mixing,meso-scale mixing,and micro-scale mixing.At a constant superficial velocity the optimal mixing was observed for a certain cohesive particle proportion.

MULTI-SCALE AGGREGATION OF PARTICLES IN GAS-SOLIDS FLUIDIZED BEDS

The multi-scale characteristics of clusters in a fast fluidized bed and of agglomerates in a fluidized bed of cohesive particles are discussed on the basis of large amounts of experiments. The cluster size and concentration are dominated by the local voidage of the bed. A cluster consists of many sub-clusters with different sizes and discrete par-ticles, and the sub-cluster size probability density distribution appears as a negative exponential function. The agglom-erates in a fluidized bed of cohesive particles also possess the multi-scale nature. The large agglomerates form a fixed bed at the bottom, the medium agglomerates are fluidized in the middle, and the small agglomerates and discrete parti-cles become the dilute-phase region in the upper part of the bed. The agglomerate size is mainly affected by cohesive forces and gas velocity. The present models for predicting the size of clusters and agglomerates can not tackle the in-trinsic mechanism of the multi-scale aggregation, and a challenging problem for establishing mechanistic model is put forward.

Measuring powder flowability with a modified Warren Spring cohesion tester

The measurement of powder flowability is a major concern for most industrial processes that deal with the handling of bulk solids as raw materials, intermediates, or products. The development of devices that measure the flowability of non-aerated powders has not progressed as rapidly as might have been hoped since most research activities have been based on various types of shear testers intended to aid the design of hoppers. A new flowability indicator named as weighted cohesion （WS） is established using newly improved version of direct cohesion texture. A cornerstone of the proposed technique is that the procedure is automated, using a digital Warren Spring tester called Warren Spring-University of Malaya cohesion tester （WSUMCT）, thus making results operator-insensitive. Besides being a practical tool to diagnose the cohesion of experimental powders, the ratio between measured cohesion （using WSUMCT） and aerated density （using Hosokawa PT-S） provides us with a powerful technique to research fundamental particle internal cohesion forces directly and use these data to indicate the flowability. In this work, a series of fine （9.4μm） and coarse （60 μm） porous silica gel particle mixtures, and mixtures of fine （28μm） and coarse （72 μm） glass ballotini as well, were used as test powders. The results from these tests agree well with relative flowability determined on our newly driven indicator using WSUMCT. The validation of aerated weighted cohesion （WSA） as a flowability indicator was authenticated by comparing the conducted parameter with established measured Hausner ratio （HR） and angle of repose （AoR）.