Search Results (29)

Sediment-laden water significantly exacerbates the cavitation damage in hydraulic machinery compared to clear water, underscoring the importance of investigating the effects of sediment on cavitation. This study examines cavitation in sediment-laden water using a Venturi flow channel and a high-speed camera system. Natural river sand samples with a median diameter of 0.05, 0.07, and 0.09 mm are selected, and sediment-laden water with a concentration of 10, 30, and 50 g/L is prepared. The results indicate that increasing the sediment concentration or reducing the sediment size intensifies cavitation, and the influence of the sediment concentration is significantly greater than that of the sediment size. Meanwhile, the numerical simulation is conducted based on a gas–liquid–solid phase mixing model. The findings indicate that a higher sediment concentration corresponds to a greater shearing effect near the wall, which raises the drag on the attached sheet-like cavitation clouds and enhances the re-entrant jet which can intensify the shedding of cavitation clouds. Furthermore, sediment particles contribute to more vortices. Therefore, for hydraulic machinery operating in sediment-laden water of high concentration, the relative velocity should be reduced to mitigate the shearing effect, thereby weakening the synergy of cavitation and sediment erosion at the turbine runner. Full article

This study investigates the force and heat transfer characteristics of oblate spheroidal particles in gas–solid two-phase flows near walls, addressing the influence of particle orientation, shape, Reynolds number, and particle–wall distance. These factors are critical in industrial processes such as pneumatic transport and crop drying, as well as in natural phenomena. Utilizing the Euler–Lagrangian model and large eddy simulation (LES), we simulated flow fields and heat transfer under various conditions. The results indicate that at Re = 500, turbulence mitigates wall interference, leading to a 14.4% increase in the Nusselt number (Nu). Particle orientation plays a crucial role in heat transfer, with Nu decreasing by 20% at = 90° due to restricted interstitial flow. A higher aspect ratio (Ar = 0.8) enhances heat transfer by 25% compared to a lower aspect ratio (Ar = 0.1). Additionally, increasing the particle–wall distance from H = 0.25$d_v$ to H = 0.5$d_v$ reduces wall-induced drag by 30%. The findings enhance the understanding of particle–fluid interactions near walls, providing a foundation for optimizing computational fluid dynamics models and improving industrial applications. Future work should consider additional variables such as particle roughness to further refine predictive capabilities. This study contributes to advancing theoretical and practical insights into non-spherical particle behaviors in complex flow environments. Full article

Gas–solid separation fluidized bed is an efficient and clean coal separation technology with a good separation effect for coal particles. However, there is a lack of systematic research on the complex motion behavior of the feeding particles in gas–solid separation fluidized beds. In this study, the separation kinetics of non-spherical single feeding particles in the fluidized bed are examined. The particle sphericity coefficient Φ is introduced to characterize the morphology of irregular coal particles, and the drag coefficient for the feeding particles is modified to verify the suitability of the non-spherical particle drag model for gas–solid fluidized bed separation. After optimization and correction, a ρ_S.sus (the bed density when single feeding particles are suspended in the gas–solid separation fluidized bed) prediction model is obtained. When the prediction accuracy of the ρ_S.sus prediction model is 90%, the confidence degree is 85.72%. This ρ_S.sus of the single non-spherical feeding particle prediction model highlights a direction for improving the separation effect, provides a theoretical basis for the industrialization of gas–solid fluidized bed, and promotes the process of dry fluidized separation. Full article

The fluidized bed is a critical reactor in the energy and chemical industries, where the mixing and agglomeration behaviors of binary particles significantly influence both the efficiency of reaction processes and the uniformity of final products. However, the selection of appropriate drag force models remains a subject of debate due to the variability in particle properties and operating conditions. In this study, we investigated the fluidization behavior of binary mixtures composed of two different sizes of Geldart-D particles within a fluidized bed, evaluating nine distinct drag force models, including Wen and Yu; Schiller and Naumann; Ergun; Gidaspow, Bezburuah, and Ding; Huilin and Gidaspow; De Felice; Syamlal and O’Brien; and Hill, Koch, and Ladd. We focused on four key parameters: particle mixing degree, migration characteristics, temperature variation, and mean pressure drop. Simulation results revealed that the choice of drag model markedly affected mixing behavior, migration dynamics, and temperature distribution. Notably, the Ergun; Gidaspow, Bezburuah, and Ding; and Hill, Koch, and Ladd models exhibited superior particle mixing uniformity. While the drag model had a relatively minor impact on particle temperature changes, its selection became critical in simulations requiring high-temperature precision. Regarding pressure drop, the Huilin and Gidaspow and Gidaspow, Bezburuah, and Ding models demonstrated smaller and more stable pressure drop fluctuations. These findings offer valuable theoretical insights into gas–solid two-phase flow under binary particle mixing and provide practical guidance for the design and operation of fluidized bed reactors. Full article

The problem of particle clogging in a conveying pipeline in thin-phase pneumatic transportation is essentially the effect of the particle-deposition mechanism in gas–solid two-phase flow. This paper presents a particle-deposition model of gas–solid two-phase flow based on the ellipsoid hypothesis, and a fast-calculation method of material particle-deposition efficiency in industry based on the tabular-assigned drag-correction coefficient of the particle ellipsoid-shape parameter $A_r$ and incoming flow angle $\varphi$. A simulation comparison of spherical particles under the same pneumatic transport conditions and experimental verification based on the self-built particle deposition system are given. The validity of the model and the accuracy of the algorithm are verified. This provides a feasible simulation and experimental scheme for the research of pneumatic-conveying technology in the industrial field. Full article

In this study, a two-dimensional computational domain featuring gas and solid phases is computationally studied for Geldart-B-type particles. In addition to the baseline case of a uniform gas-phase injection velocity, three different inlet velocity profiles were simulated, and their effects on the fluidized bed hydrodynamics and bubble dynamics have been studied. An in-house computer program was developed to track the bubbles and determine the temporal evolution of their size and position prior to their breakup. This program also provides information on the location of bubble coalescence and breakup. The gas-solid interactions were simulated using a Two-Fluid Model (TFM) with Gidaspow’s drag model. The results reveal that the bed hydrodynamics feature a counter-rotating vortex pair for the solid phase, and bubble dynamics, such as coalescence and breakup, can be correlated with the vortices’ outer periphery and the local gradients in the vorticity. Full article

Fluidization bed reactor is an attractive method to synthesize and process quantities of functional nanoparticles, due to the large gas–solid contact area and its potential scalability. Nanoparticles fluidize not individually but as a form of porous agglomerates with a typical porosity above 90%. The porous structure has a significant effect on the hydrodynamic behavior of a single nanoparticle agglomerate, but its influence on the flow behavior of nanoparticle agglomerates in a fluidized bed is currently unclear. In the present study, a drag model was developed to consider the porous structure effects of nanoparticle agglomerates by incorporating porous-structure-based drag laws in the Eulerian–Eulerian two-fluid model. Numerical simulations were performed from particulate to bubbling fluidization state to evaluate the applicability of porous-structure-based drag laws. Results obtained for the minimum fluidization and bubbling velocities, bed expansion ratio, and agglomerate dispersion coefficient show that, compared with the drag law of solid sphere, the porous-structure-based drag laws, especially the drag law of fractal porous spheres, provide a closer fit to the experimental data. This indicates that the pore structures have a great impact on gas–solid flow behavior of nanoparticle agglomerates, and the porous-structure-based drag laws are more suitable for describing flows in nanoparticle agglomerate fluidized beds. Full article

Based on the two-fluid model, a three-zone drag model was developed, and the kinetic theory of granular flows and the Schneiderbauer solids wall boundary model were modified to establish a new three-dimensional (3D) unsteady mathematical model for high-pressure dense-phase pneumatic conveying in horizontal pipe. With this mathematical model, the influence of the three frictional stress models, namely Dartevelle frictional stress model, Srivastava and Sundaresan frictional stress model, and the modified Berzi frictional stress model, on the simulation result was explored. The simulation results showed that the three frictional stress models accurately predicted the pressure drop and its variations with supplementary gas in the horizontal pipe, with relative errors ranging from −4.91% to +7.60%. Moreover, the predicted solids volume fraction distribution in the cross-section of the horizontal pipe using these frictional stress models exhibited good agreement with the electrical capacitance tomography (ECT) images. Notably, the influence of the three frictional stress models on the simulation results was predominantly observed in the transition region and deposited region. In the deposited region, stronger frictional stress resulting in lower solids volume fraction and a higher pressure drop in the horizontal pipe were observed. Among the three frictional stress models, the simulation results with the modified Berzi frictional stress model aligned better with the experimental data. Therefore, the modified Berzi frictional stress model is deemed more suitable for simulating high-pressure dense-phase pneumatic conveying in horizontal pipe. Full article

In this work, the influence of gas–solid drag and heat transfer coefficient models on the prediction capacity of the Euler–Euler approach to simulate reactive bubbling fluidized bed flows is studied. Three different cases are considered, a non-reactive bidisperse bubbling fluidized bed flow (Case 1), and two reactive polydisperse flows in bubbling fluidized beds, one for biomass gasification (Case 2), and the other for biomass pyrolysis (Case 3). The Gidaspow, Syamlal–O’Brien, and BVK gas–solid drag models and the Gunn, Ranz–Marshall, and Li–Mason gas–solid heat transfer correlations are investigated. A Eulerian multiphase approach in a two-dimensional Cartesian domain is employed for the simulations. Computational results for the three cases are compared with experimental data from the literature. The results obtained here contribute to a better understanding of the impacts of such closure models on the prediction ability of the Euler–Euler approach to simulate reactive flows. The results indicate that, for the simulation of reactive flows in bubbling fluidized bed reactors, the kinetic modeling of the reactions has a global effect, which superposes with the influence of the drag and heat transfer coefficient models. Nevertheless, local parameters can be noticeably affected by the choice of the interface closure models. Finally, this work also identifies the models that lead to the best results for the cases analyzed here, and thus proposes the use of such selected models for gasification and pyrolysis processes occurring in bubbling fluidized bed reactors. Full article

The discrete element method (DEM) coupled with computational dynamics (CFD) has been considered one of the most sensitive ways of studying the micro fluidized bed. This article proposes a so-called particle circumstance-dependent drag model that is dependent on a particle’s complex circumstances. Slugging and non-slugging fast fluidization in a micro fluidized bed is modeled with the use of the CFD-DEM. The results show that the formation and the fragmentation of clusters in a slugging fast fluidized state are clearly captured, and both have time synchronization. However, with the increase in gas velocity, the boundary of the dense and dilute phases turns blurry and the slugs disappear. Furthermore, there exists a relatively serious backmixing of particles in the slugging fast fluidization, while the backmixing effect weakens in the non-slugging fast fluidization. Moreover, the outlet solid flux decreases compared with those in the big fluidized beds for the slugging fast fluidized bed due to the micro size effect, while the micro size effect on the solid flux is not distinct for the non-slugging fast fluidized bed. Last but not least, the radial porosity with slugging exhibits a weakened core-annulus structure compared with the correlated radial porosity in the big fluidized beds. The radial porosity without slugging tends to approach the correlated core-annulus structure. Full article

Severe erosion phenomena often occur in industrial polycrystalline silicon units, leading to hydrogen leakage accidents and affecting long-term operation. It is favorable to use a computational fluid dynamics (CFD) simulation with the dense discrete phase model (DDPM) and the sub-grid energy-minimization multi-scale (EMMS) drag model to improve the prediction accuracy of complex multiphase erosion phenomena in a connecting pipe of an industrial polycrystalline silicon unit. Furthermore, the effect of droplet the specularity coefficient on boundary conditions is thoroughly considered. The predicted erosion behaviors are consistent with industrial data. The effects of operations parameters were discussed with three-dimensional CFD simulation, including droplet size and hydrogen volume fraction on erosion behaviors. The results indicated that the non-uniform multiphase erosion flow behavior near the wall can be simulated accurately with the EMMS drag model in a coarse mesh. A suitable droplet specularity coefficient such as 0.5 can also improve the accuracy of erosion position. Small liquid droplets, such as those of 30 μm size, will follow the gas phase better and have a lower erosion rate. The inertia effect of large droplets, such as those of 150 μm size, plays a dominant role, resulting in obvious erosion on the elbow walls. The erosion range and thinning rate enlarge with the increase in hydrogen volume fraction. A few silicon solid particles, such as 0.01% volume fraction, change local flow behaviors and probably cause the variation of local erosion positions. The process of erosion deformation first circumferentially extended and then accelerated at the local center position deeper. Full article

In recent years, the discrete element method (DEM) has gradually been applied to the traditional fluidization simulation of fine particles in a micro fluidized bed (MFB). The application of DEM in the simulating fast fluidization of fine particles in MFB has not yet received attention. This article presents a drag model that relies on the surrounding environment of particles, namely the particle circumstance-dependent drag model or PCDD model. Fast fluidization in an MFB of fine particles is simulated using DEM based on the PCDD model. Simulations indicate that the local structure in an MFB exhibits particle aggregation, which is a natural property of fast fluidization, forming a structure where a continuous dilute phase and dispersed concentrated phase coexist. There exists a strong effect of solid back-mixing in an MFB, leading to relatively low outlet solid flux. The gas back-mixing effect is, however, not so distinct. The axial porosity shows a monotonically increasing distribution with the bed height but does not strictly follow the single exponential distribution. The solid volume fraction at the bottom of the bed is significantly lower than the correlated value in CFB. The axial heterogeneous distribution of the cross-sectional average porosity in the lower half of the bed is also weakened. The radial porosity shows a higher distribution pattern in the central region and a lower one in the sidewall region. Full article

Most granular flow in nature and industrial processing has the property of polydispersity, whereas we are always restricted to using the monodisperse drag force model in simulations since the drag force model with polydispersity is difficult to establish. Ignoring polydispersity often results in obvious deviations between simulation and experimental outcomes. Generally, it is very hard for us to describe the characteristics of polydispersity in drag force by using a function with analytic expression. Recently, the artificial neural network (ANN) model provides us the advantages of estimating these kinds of outcomes with better accuracy. In this work, the ANN is adopted to model the drag force in polydisperse granular flows. In order to construct a reasonable ANN algorithm for modeling the polydisperse drag force, the structures of ANN are elaborately designed. As training for the ANN drag model, a direct numerical simulation method is proposed, based on the lattice Boltzmann method (LBM), to generate the training data, and an adaptive data filtering algorithm, termed as the optimal contribution rate algorithm (OCRA), is introduced to effectively improve the training efficiency and avoid the over-fitting problems. The results support that the polydispersity of the system can be well scaled by the ANN drag model in a relatively wide range of particle concentrations, and the predicted results coincide well with the experimental ones. Moreover, the ANN drag model is not only effective for polydisperse systems, but compatible with monodisperse systems, which is impossible using traditional drag models. Full article

Objective of this study is to investigate the effect of secondary motion of particles in multiphase gas-solid flows parametrically and test the relative impacts of particle shape and orientation information on particle distribution. For that purpose, predictive accuracies of simplified drag coefficient models are assessed for the conditions relevant to a wood recovery plant operating at dilute flow regime. After demonstrating the strong impact of the shape and orientation information on the force balance for single particles, we compared the steady state Eulerian-Lagrangian simulation results for particle volume fractions, residence times and particle diameter distributions within the chamber for different (i) superficial gas velocities (5 m/s, 7.5 m/s), (ii) orientation tendencies and (iii) particle shapes. Transient simulations are performed until the system reaches steady state conditions by monitoring the mass flow rates of the particulate phases leaving the chamber. The secondary motion of non-spherical particles is represented by stochastic sampling from the available experimental data. Analysis of the force balance on single particles revealed log-scale variations if the orientation of the particles with respect to flow fluctuates. Variations in the single particle force balances are found to be still visible in the CFD analysis, where the secondary motion of particles drastically changed the particle distribution in the chamber. The native non-spherical model which only accounts for the shape correction was found to over-predict the entrainment, leading to a significantly different particle volume fraction and diameter distributions. Spherical particle assumption also caused significant errors in the particle distribution, which increases as aspect ratio of the cylindrical particle diverges from one. Results show that particle orientation statistics are extremely important to capture the particle mixing and segregation patterns at dilute regime, which cannot be captured with such simplifying assumptions. Full article

In many process engineering fields, gas-particle fluidized beds are widely used. In fluidized bed research, the discrete element method, or DEM, has been a powerful tool for design and operation purposes. However, with the use of Type-A powders, fluid catalytic cracking or FCC particles being classical cases, they have hardly been reported in DEM simulations of fast fluidization. This study paid close attention to the suitable selection of a stiffness constant and a DEM time step. To reflect their respective effects and complicated interactions, a so-called relative DEM time step was defined. The drag coefficient was correlated using the energy-minimization multi-scale (EMMS) approach to reasonably calculate the gas–solid interaction. Six representative cases with different relative time step values were chosen to simulate a micro-fluidized bed of Type-A FCC powders. The results showed that DEM employing EMMS-based drag force was able to greatly enlarge the suitable range of relative time steps in a fast fluidization simulation of Type-A powders. In addition, the typical macro flow structures of fast fluidization was successfully captured: axially dilute in the top and dense in the bottom, and radially dilute in the core and dense near the wall. Moreover, the distinct gas–solid backmixing, which is considered one of the most important pieces of evidence for the determination of fast fluidization regimes, was modeled. It was indicated that the EMMS-based drag model attenuated the overestimated drag force so that the soft-sphere contact model would be able to more appropriately deal with particle collision, and thus improve the suitable relative DEM time step range. Full article