CFD simulation and experimental validation of nanoparticles fluidization in a conical spouted bed

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Highlights

  • Influence of drag models and solid wall boundary conditions are considered.

  • The RUC model predicts the pressure drop values more accurately.

  • The CFD model suitably predicts the behavior of the spouting regime.

  • Choice of drag models can significantly affect the hydrodynamics of fluidization.

Abstract

In the present study, hydrodynamic parameters of micro/nanoparticles in a conical spouted bed were investigated using experimental and computational fluid dynamics (CFD) techniques. The Eulerian–Eulerian approach, in conjunction with the kinetic theory of granular flow (KTGF) has been used, and the effects of solid wall boundary condition parameters such specularity coefficient (φ), and particle-wall restitution coefficient (ew), on the hydrodynamics of the bed were studied. The effect of drag force on the fluidization behavior of nanoparticles was investigated using Gidaspow and RUC drag models, and the results showed the superiority of the RUC model. Experiments were carried out for measuring the pressure drop in a lab-scale conical spouted bed. The CFD predictions were in good agreement with the experimental data in terms of pressure drop and particle distribution.

Introduction

The conical spouted beds as efficient gas-solid contractors have been widely used in various industrial processes, including drying, separation, gasification, and oxidation (Hosseini et al., 2018a; Altzibar et al., 2014; Saldarriaga et al., 2015; Mostoufi et al., 2015). The conical spouted beds have also been successfully used in the pyrolysis of wastes, specifically biomass, plastics, and tires. Compared to conventional fluidized beds, the conical spouted beds have useful features due to their excellent performance in handling sticky and irregular materials, such as biomass and scrap tires (San José et al., 2014). The main advantages of the conical spouted beds are the high gas velocities, high heat and mass transfer rates, and good particle movement (Park et al., 2019). Moreover, according to the high gas velocities, vigorous gas-solid contact is generated and avoids bed de-fluidization by agglomeration of particles, even under conditions where the system involves very adhesive or sticky particles, such as fine particles, waste tires, or plastics (Lopez et al., 2010).

During fluidization, solid particles are thrown up with inlet gas at high speed by an orifice embedded in the bottom of the column, thus creating a proper mixing between the gas and solid particles (Hosseini et al., 2018b). The fluidization behavior depends on some different parameters, most importantly, the size and density of the particles. The particle size varies from macro-sized (several millimeters down to several microns) to nano-sized particles (Wang et al., 2007). The particle size classification is based on the Geldart standardization (Geldart, 1973). According to Geldart’s classification, the particles are divided into four groups, i.e., A, B, C, and D, based on their fluidization behavior. Group A with the particle size of 20−100 μm, group B with the particle size of 40−500 μm, Group C contains extremely fine and consequently the most cohesive particles, and group D that is called ‘spoutable’ and the particles are either very large or very dense (Sun et al., 2017; Zhu et al., 2016).

Extensive studies have been conducted in the past in the field of fluidization behavior of classical powders (Geldart group A and B particles). However, according to the complex fluidization behavior of nanoparticles, less research has been performed in this field (Zhu et al., 2005). Due to strong van der Waals, capillary, liquid bridging, and electrostatic forces between the nanoparticles, they tend to attach to each other and form strong and large agglomerates, which the agglomerates structures may change during the fluidization (Tamadondar et al., 2016). Based on the Geldart’s classification, extremely fine particles would be very cohesive and challenging to fluidize, and by decreasing the particle size, the cohesive forces increases. Therefore, it can be said that the nanoparticles are difficult to fluidize, so the fluidization behavior is complex, and they can be fluidized in the form of agglomerates (Nam et al., 2004).

According to experimental observations, the nanoparticles have two distinct fluidization regimes, termed agglomerate particulate fluidization (APF) and agglomerate bubbling fluidization (ABF) (Quevedo et al., 2007). The APF shows bubble-less smooth fluidization with high bed expansion, and the ABF refers to a large bubbles fluidization with low bed expansion.

Based on the experimental data reported by Zhu et al., the difference between APF and ABF depends on the bulk density and the primary particle size (Zhu et al., 2005).

Yao et al. (2002) studied the fluidization of six kinds of SiO2 nanoparticles with sizes from 7 to 16 nm, and the APF behavior and the bed expansion of nanoparticles are investigated. According to their results, the agglomerates structure, the size, the interactive forces, and apparent weight significantly influence the agglomerating fluidization.

In the field of CFD modeling, even though many aspects of the fluidization behavior of classical particles have been studied (Deen et al., 2007; Du et al., 2006a; Duarte et al., 2005; Hosseini, 2016), few studies have focused on modeling of the nanoparticle fluidization.

Liu et al. (2016) studied nanoparticle fluidization by using adhesive CFD-DEM (Discrete Element Model) simulation. The effects of gas velocity, particle density, and van der Waals force on gas-solid flow and agglomerate fluidization are investigated. Due to the results, by increasing the fluidizing gas velocity and reducing the particle adhesion, the agglomerate breakage rate increases.

Huilin et al. (2010) performed two-dimensional simulations of gas and agglomerates flows in gas–cohesive particles fluidized beds. Distribution of axial velocity of Tullanox nanoparticles, the concentration of particle agglomerates, and the diameter of agglomerates are predicted in fluidized beds. Their model has shown promise to be a useful tool to simulate gas-particle agglomerates flows.

Wang et al. (2015) performed numerical simulations on the behavior of agglomerates of nanoparticles in bubbling gas fluidized beds and spouted beds. An Eulerian two-fluid approach has been used, and the cohesive force between particles has been considered in the models. According to their results, a high spouting gas velocity is required to fluidize the agglomerates in the spouted bed.

Yu et al. (2006) studied the fluidization of carbon nanotubes (CNTs) in a nano-agglomerate fluidized bed (NAFB). Their results showed that the pattern of CNT fluidization is close to the ABF characteristics, however in the range 0.017−0.038 m/s of gas velocities, the particulate fluidization behavior could also be achieved.

The literature reviews reveal a lack of a comprehensive CFD analysis of the nanoparticles fluidization in the conical spouted beds. The impact of the effective parameters of the solid-wall boundary condition on the hydrodynamics of nanoparticles in the spouted beds has not been evaluated so far. Therefore, in the present study, the hydrodynamics performance of a conical spouted bed containing nanoparticles is investigated using both experimental and CFD techniques. Besides, the effect of drag models, and solid wall boundary conditions, i.e., specularity coefficient (φ) and particle-wall restitution coefficient (ew), on the hydrodynamics of nanoparticles are studied.

Section snippets

Experimental set up

Fig. 1 shows a schematic diagram of the experimental setup. It consists of a conical spouted bed, which is equipped with a highly accurate manometer, mass flow meter, and a high-speed camera. The spouted bed consists of a Plexiglas column with an upper diameter (Dc) of 90 mm, and a cone angle of 60°. The cone height (Hc) is 70 mm, and the total height of the column (HT) is 500 mm. An inlet gas nozzle (Di) of 5 mm in diameter is located at the center of the cone bottom. The accurate manometer

CFD analysis

Computational fluid dynamics (CFD) techniques are concerned with the numerical solution of equations of fluid flow as well as with the interaction of the fluid/particles with solid walls. In this work, CFD has been used to investigate the fluidization behavior of micro/nanoparticles in a conical spouted bed. Turbulent incompressible fluid flow, without mass transfer and chemical reaction under transient conditions were assumed.

The commercial CFD package ANSYS FLUENT, version 16, was used to

Model validation

To validate the CFD simulation of micro/nanoparticles behavior in a conical spouted bed, the experiments under various operating conditions are conducted. The solid particle distribution through the bed is one of the essential hydrodynamics parameters, which is widely used in the design of the conical spouted beds. In the experiments, the volume fraction of solid particles through the bed is obtained for the bed of sand A, sand B, and alumina nanoparticles. An initial particle bed height of 55

Conclusion

The hydrodynamics parameters of a conical spouted bed were studied using experimental and CFD techniques. Two-fluid models, in conjunction with the kinetic theory of granular flow, have been used for investigation of the fluidization behavior of micro and nanoparticles. Effects of spouting gas velocity, and drag force models, as well as solid wall boundary conditions on the bed pressure drop and fluidization behavior, were investigated. For validation of the CFD predictions, the simulation

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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