CFD simulation and optimization of the flow field in horizontal turbo air classifiers

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

This article describes the methodology used to identify the mathematical equation that describes the correlations between the input and output parameters of an experiment. As a technological process, aerodynamic separation was chosen to represent the behavior of a solid particle within an ascending vertical airflow. The experimental data were used to identify two parameters, namely the average linear velocity and the angular velocity. The Table Curve 3D program was used to develop a mathematical equation describing the dependence between the input parameters (the shape and size of the solid particle, as well as the velocity of the airflow) and the monitored parameters. A pyramid-type analysis (following a filtering system, a general equation was determined from a large number of equations that characterize an experimental set mathematically) was designed in order to determine a single mathematical equation that describes the correlation between the input variables and those obtained as accurately as possible. The determination of the mathematical equation started with the number of equations generated by the Table Curve 3D program; then, the equations with a correlation coefficient greater than 0.85 were chosen; and finally, the common equations were identified. Respecting the working methodology, one equation was identified, which has for the average linear velocity, a correlation coefficient r2 of between 0.88–0.99 and 0.86–0.99 for the angular velocity.

Effects of a Guide Cone on the Flow Field and Performance of a New Dynamic Air Classifier

A new dynamic air classifier was designed to address the problems of uneven material dispersion and high dust concentration in industrial applications of turbo air classifiers. This paper presents a study on the use of guide cones in the new dynamic air classifier. The ANSYS-Fluent 19.2 software was implemented to simulate the airflow in the dynamic air classifier, and the impact of the guide cone size on the flow field and classification performance of the dynamic air classifier was investigated. The simulation results indicated that with the increase in the guide cone height, the flow field distribution becomes reasonable and the velocity distributions become uniform. When the guide cone height is greater than twice the distance between the guide cone and the bottom of the rotor cage, there is no discernible change in the flow field distribution and classification efficiency. When the guide cone diameter is approximately 0.9 times the diameter of the rotor cage, the airflow pathline is more reasonable, and the flow field and velocity distributions are more uniform. An improper guide cone diameter and height will worsen the classification environment, resulting in a significant decline in classification performance. The material experimental and discrete phase simulation (DPM) showed that DPM can anticipate the changing trends of the cut size and classification accuracy. This study provides theoretical assistance for the structural design and optimization of an air classifier.

Numerical and Experiment Investigation on Novel Guide Vane Structures of Turbo Air Classifier

In this paper, three types of air guide vanes are designed: direct-type, L-type, and logarithmic spiral type, respectively. ANSYS-FLUENT 20.0 is used to numerically simulate the internal flow field of turbo air classifier by novel different structures. The numerical results show that the guide vane structures have a good effect on the flow field stability of the annular function zone in the classifying chamber. The distribution of tangential velocity and radial velocity verified the logarithmic spiral guide vane, and makes the airflow flow along the rotor cage circumferentially uniformly. In addition, the turbulent dissipation rate and energy loss decreases in the rotor cage region, which also shows that the guide vane is beneficial to improve classification performance. The tromp curve of the numerical simulation shows that the logarithmic spiral guide vane reduced the cutting size by 6.3% and 23.7% at two different process parameters, and is obviously better than other guide vane structures in improving the classification sharpness index (K). Finally, the reliability of numerical simulation is verified by material experiment. The research results have certain theoretical significance and guidance for the structural design of the guide vanes of the turbo air classifier.

Development of a Model for the Separation Characteristics of a Deflector Wheel Classifier Including Particle Collision and Rebound Behavior

Deflector wheel classifiers are widespread in industry for the separation of powders into fine and coarse powders. Even though this separation process has been known for quite some time, it is not yet fully understood, and existing models fail to precisely predict the separation characteristics. Due to the high throughput of deflector wheel classifiers, it is greatly beneficial to estimate the separation characteristics before the experiment. Here, the developed model critically examines the usual assumptions, such as ideal airflow, neglection of particle–wall and particle–particle interactions, or spherically-shaped particles. First, the investigation of the air flow using a Particle Image Velocimetry (PIV) system showed significant differences to the assumed ideal flow field, then particle sphericity and its influence on the interaction between the particles and the paddles of the deflector wheel was investigated and compared with particle rebound behavior on a static wall. Surprisingly, comminuted glass behaves similarly to comminuted limestone in multiple aspects and not like glass beads. To determine the number of particle–particle collisions, Discrete Element Method (DEM) simulations were performed. The aforementioned aspects found application in the model and the separation behavior was well-estimated.

CFD-Based Structural Optimization of Rotor Cage for High-Efficiency Rotor Classifier

Due to the uneven materials dispersion and high dust concentration in industrial applications of turbo air classifiers, a high-efficiency rotor classifier was designed. Numerical simulations by ANSYS-Fluent 19.0, the effects of rotor cage shape, the number of blades, and the blade profile on the inner flow field, as well as classification performance, were investigated. The simulation results indicated a significant improvement in flow field distribution near the classification surface with the conical rotor cage. Furthermore, there was an average reduction of 10.1% in cut size, as well as a 23.6% increase in classification accuracy. When the number of blades was 36, the flow field distribution between the blades was relatively uniform and a smaller cut size was obtained at a higher classification accuracy. A streamline blade with 52° as the inlet installation angle effectively reduced the impact of the airflow on the blade and eliminated the inertia anti-vortex between blades. The cut size reduction was 4.7–6.3%, with a basically unchanged classification accuracy. The material classification experimental results were in agreement with the simulated results. The discrete phase model (DPM) could well-predict the cut sizes and classification accuracy, but it could not present the fishhook effect. The present study provides theoretical guidance for the structural optimization of an air classifier with a rotor cage.

A New Rotor-Type Dynamic Classifier: Structural Optimization and Industrial Applications

Due to the inadequate pre-dispersion and high dust concentration in the grading zone of the turbo air classifier, a new rotor-type dynamic classifier with air and material entering from the bottom was designed. The effect of the rotor cage structure and diversion cone size on the flow field and classification performance of the laboratory-scale classifier was comparatively analyzed by numerical simulation using ANSYS-Fluent. The grinding process performance with an industrial classifier was also tested on-site. The results revealed that an inverted cone-type rotor cage is more suitable for the under-feed classifier. When the rotor cage’s top-surface diameter to bottom-surface diameter ratio was too large or too small, the radial velocity and tangential velocity at the outer surface of the rotor cage greatly fluctuated. Furthermore, the diameter of the diversion cone also affected the axial velocity and radial velocity of the flow field. Models T-C(1-0.8) and T-D(1-0.7) were determined as the best rotor cage structures. Under stable operating conditions, the classification efficiency of the industrial classifier was 87% and the sharpness of separation was 0.58, which meet the industrial requirements for classification efficiency and energy consumption. This present study provides theoretical guidance and engineering application value for air classifiers.

Ring-Shaped Baffle Effect on Separation Performance of Lithium Carbonate Micro Particles in a Centrifugal Classifier

In this work, a centrifugal classifier for separating lithium carbonate particles, used as a cathode material for lithium-ion batteries, was investigated. This work numerically evaluates the internal flow and particle separation performance of the centrifugal classifier. The complex turbulent flow field in the classifier is key to understanding particle motion. A Reynolds stress model, to describe air flow field, and a discrete phase model, to track particle motion, were applied to a numerical simulation. Design parameters such as mass flow rate and rotor speed were investigated, and a ring-shaped baffle, in particular, was designed to investigate the effects of flow and particle separation in the centrifugal classifier. The simple geometry of the baffle changes the movement direction of unseparated particles to the rotor cage region, and increases the local air velocity in the separation zone. The numerical analysis results were verified through a baffle experiment.

Numerical Simulation of a Flow Field in a Turbo Air Classifier and Optimization of the Process Parameters

Due to the rapid development of powder technology around the world, powder materials are being widely used in various fields, including metallurgy, the chemical industry, and petroleum. The turbo air classifier, as a powder production equipment, is one of the most important mechanical facilities in the industry today. In order to investigate the production efficiency of ultrafine powder and improve the classification performance in a turbo air classifier, two process parameters were optimized by analyzing the influence of the rotor cage speed and air velocity on the flow field. Numerical simulations using the ANSYS-Fluent Software, as well as material classification experiments, were implemented to verify the optimal process parameters. The simulation results provide many optimal process parameters. Several sets of the optimal process parameters were selected, and the product particle size distribution was used as the inspection index to conduct a material grading experiment. The experimental results demonstrate that the process parameters of the turbo air classifier with better classification efficiency for the products of barite and iron-ore powder were an 1800 rpm rotor cage speed and 8 m/s air inlet velocity. This research study provides theoretical guidance and engineering application value for air classifiers.