Experimental investigation on separation characteristics of axial cyclone separator

Gas-liquid two-phase flow in rectangular channels involves thermal energy, chemical industry, and other fields. However, it is difficult to identify steady flow status and unify heat transfer model owing to the changeable mixing process and the complex industrial environment. In this work, the time series decomposition technique (i.e., variational mode decomposition) and neural network algorithm (i.e., long short-term memory) are employed to identify the steady flow pattern of the gas-liquid mixing process in vertical rectangular channels. The heat transfer model of a single bubble in a rectangular channel is established based on the geometrical characteristics of the bubble. Results demonstrate that a 30-dimensional feature vector is extracted from the conductivity time series for flow pattern recognition. The feature parameters of each intrinsic mode function are period, minimum, maximum, standard deviation, skewness, and kurtosis. Average accuracy of the new model is 94.58% with the highest at 95.83% and the proposed new model improves the recognition accuracy of steady flow pattern by 2.54–6.93% compared with other models adopted in this work. The precision of the new hybrid model is the highest while the number of decomposition layers for the conductivity time series is 5 and the bubble flow exhibits the largest heat transfer area under the same conditions. The proposed hybrid model can be used to enhance the identification accuracy of bubble flow in rectangular channels, contributing to curtailing unneeded flow patterns in industrial processes. The heat transfer model of a single bubble can provide a unified and convenient method for calculating industrial heat transfer. These findings provide a useful guideline for engineering design and energy-saving in the fields of thermal energy and chemical industry. 

A unified heat transfer model for gas-liquid two-phase mixing process in a rectangular channel based on steady status identification

GPU-powered CFD-DEM framework for modelling large-scale gas–solid reacting flows and an industry application

Exploring the kinetic characteristics and internal thermochemical behavior of the raceway is essential to provide in-depth insights and valuable references for the actual blast furnace (BF) production. In this paper, the flow, heat and mass transfer behaviors and kinetic characteristics of coke particles in the BF raceway were modelled using Discrete Element Method-Computational Fluid Dynamics (DEM-CFD) method from particulate scale. The effects of process parameters (blast velocity/temperature, and oxygen concentration) on gas species distribution, reaction kinetic rate, particle temperature, particle size, dynamic characteristics (raceway size, kinetic energy) and microscopic properties (coordination number, contact force, total force, and pore distribution) were systematically investigated. On this basis, the back propagation neural network (BPNN) model was established to predict raceway size for any combination of process parameters. The results show that blast velocity/temperature and oxygen concentration have strong influences on the reaction kinetic rate, gas species distributions and microscopic properties of the coke bed. Higher blast velocity or temperature makes the higher temperature and carbon loss of individual coke particles around the raceway, and the mass transfer between gas and coke particles is not diminished due to the excessive oxygen at a large oxygen concentration. The width and height of the raceway increase with the increase of blast velocity and oxygen concentration. The BPNN model can well predict the raceway size, which provides a quick and easy way to establish a more accurate and effective strategy for raceway size control. 

DEM-CFD investigation on the blast furnace raceway characteristics: Heat/mass transfer, dynamics and mechanisms

An in-depth exploration of the reaction kinetics and thermo-chemical behaviors of the raceway can offer practical insights for optimizing the operations of blast furnace (BF), thus achieving a more effective iron and steel production process. In this study, the dynamic characteristics and the flow, heat and mass transfer behaviors in the BF raceway were simulated by Discrete Element Method-Computational Fluid Dynamics (DEM-CFD) method at a particulate scale. The effects of coke size distribution and blast velocity on coke combustion characteristics, thermochemical behavior (particle volume fraction, raceway size, carbon loss, and coke temperature) and microscopic properties (coordination number (CN), contact normal force, pore structure and stress) were systematically investigated. The results show that as the blast velocity decreases or the size ratio λ (the largest coke particle size divided by the smallest coke particle size) increases, the raceway size becomes smaller, resulting in a smaller area of high oxygen (O2) concentration and low carbon monoxide (CO) concentration in the raceway, and higher CO concentration in the packed bed. For the thermal-chemical behaviors, a lower blast velocity or a higher λ value decreases the number of particles experiencing mass loss, as well as increases individual particle mass loss, the average coke temperature and its variance. For microscopic properties, the CN distribution becomes wider as λ increases. The contact normal force in the coke bed with λ > 1 is significantly higher than that of λ = 1. As λ increases or blast velocity decreases, the pore distribution curve shifts to the left and the average pore volume decreases. The stress acting on the particles in the raceway increases with the blast velocity or λ. These new understandings of the complex reactive flow behaviors in the raceway will shed light on energy utilization and process optimization. 

Effects of particle size distribution and blast velocity on furnace raceway transport behaviors and dynamic characteristics using DEM-CFD

Particle-scale modelling of injected hydrogen and coke co-combustion in the raceway of an ironmaking blast furnace

Investigation on separation characteristics of gas–liquid two-phase flow around the perforated tube

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Particle-scale modelling of injected hydrogen and coke co-combustion in the raceway of an ironmaking blast furnace

Investigation on separation characteristics of gas–liquid two-phase flow around the perforated tube