Computational Fluid Dynamics Discrete Element Method Research Articles

The Development of a Multiphysics Coupled Solver for Studying the Effect of Dynamic Heterogeneous Configuration on Particulate Debris Bed Criticality and Cooling Characteristics

For a sodium-cooled fast reactor, the capability for stable cooling and avoiding re-criticality on the debris bed is essential for achieving in-vessel retention when severe accidents occur. However, an unexploited uncertainty still existed regarding the compound effect of the heterogeneous configuration and dynamic particle redistribution for the debris bed’s criticality and cooling safety assessment. Therefore, this research aims to develop a numerical tool for investigating the effects of the different transformations of the heterogeneous configurations on the debris bed’s criticality/cooling assessment. Based on the newly proposed methodology in this research, via integrating the Discrete Element Method (DEM) with Computational Fluid Dynamics (CFD) and Monte-Carlo-based Neutronics (MCN), the coupled CFD–DEM–MCN solver was constructed with the originally created interface to integrate two existing codes. The effects of the different bed configurations’ transformations on the bed safety assessments were also quantitively confirmed, indicating that the effect of the particle-centralized fissile material had the dominant negative effect on the safety margin of avoiding re-criticality and particle re-melting accidents and had a more evident impact than the net bed-centralized effect. This coupled solver can serve to further assess the debris bed’s safety via a multi-physics simulation approach, leading to safer SFR design concepts.

A coarse graining CFD–DEM simulation on contact erosion of layered cohesionless soils

A coarse graining computational fluid dynamics–discrete element method (DEM) model is developed to analyze the contact erosion of cohesionless soils at the coarse/fine soil interface. Two benchmark cases are provided to verify the model implementation, including the collision of two groups of particles and collapse of a soil column in water. It is demonstrated the CG approach significantly reduces the computational cost with sufficiently good accuracy. Two typical CG approaches, i.e., the relative overlap scaling (ROS) and absolute overlap scaling approaches, are compared and show similar model performance. While the DEM time step of ROS approach is scaled up by the scaling factor, it is recommended in this study for the better computational performance. The verified model is used to simulate the laboratory contact erosion experiment under various flow conditions. The critical discharge rate calculated from the numerical model is 357 mL/s, which achieves a high consistency with the experimental value of 311 mL/s. Further study shows the scaling factor influences the critical discharge rate, as large parcels introduce boundary effects especially for coarse soils. It is also shown the packing state of coarse soils is a determinant in the erosion initiation, as the void fraction distribution is the key for particle and fluid transports, especially near the contact surface.

Computational fluid dynamics-discrete element method simulation of stirred tank reactor for graphene production

Liquid phase exfoliation (LPE) process for graphene production is usually carried out in stirred tank reactor and the interactions between the solvent and the graphite particles are important as to improve the production efficiency. In this paper, these interactions were revealed by computational fluid dynamics–discrete element method (CFD-DEM) method. Based on simulation results, both liquid phase flow hydrodynamics and particle motion behavior have been analyzed, which gave the general information of the multiphase flow behavior inside the stirred tank reactor as to graphene production. By calculating the threshold at the beginning of graphite exfoliation process, the shear force from the slip velocity was determined as the active force. These results can support the optimization of the graphene production process.

Comparative analysis on gas–solid drag models in MFIX-DEM simulations of bubbling fluidized bed

In this study, the open-source software MFIX-DEM simulations of a bubbling fluidized bed (BFB) are applied to assess nine drag models according to experimental and direct numerical simulation (DNS) results. The influence of superficial gas velocity on gas–solid flow is also examined. The results show that according to the distribution of time-averaged particle axial velocity in y direction, except for Wen–Yu and Tenneti–Garg–Subramaniam (TGS), other drag models are consistent with the experimental and DNS results. For the TGS drag model, the layer-by-layer movement of particles is observed, which indicates the particle velocity is not correctly predicted. The time domain and frequency domain analysis results of pressure drop of each drag model are similar. It is recommended to use the drag model derived from DNS or fine grid computational fluid dynamics–discrete element method (CFD-DEM) data first for CFD-DEM simulations. For the investigated BFB, the superficial gas velocity less than 0.9 m·s−1 should be adopted to obtain normal hydrodynamics.

Clogging and permeability reduction dynamics in porous media: A numerical simulation study

The dynamics of fine particle entrainment, transport, and deposition within pore systems, and in particular, the capacity for mobile fines to impair permeability within porous media is critical in many industrial applications. Considerable effort has been expended over the past several decades to identify and parametrize the governing factors that control permeability reduction, with studies employing a combination of physical experimentation and numerical simulation toward this aim. The objective of this work was to numerically investigate the impact of pore space geometry and fine sizes on the clogging dynamics of porous media. The clogging dynamics were characterized by the length of clogging zone (LCZ), the critical throat size of clogging (CTZC), the clogged fraction of throats (CFT), and the permeability reduction (PR). We implemented a computational fluid dynamics-discrete element method (CFD-DEM) numerical framework with a four-way coupling scheme to obtain insights into throat clogging and permeability reduction within heterogeneous porous media utilizing four different monodisperse suspensions. Geometries of porous media were extracted from 3D images of sand packs obtained using micro-computed tomography. The geometries had porosity values ranging from 0.35 to 0.57 and initial permeabilities between 1.35 and 26.32 μm2. CFD-DEM simulations were performed on each geometry four times, varying the injected fine particle size from 5 to 15 μm diameters. Findings indicate that pore systems with tortuosity <1.28 and angles of solid grains orientation larger than 46o tend to have shorter length clogging zones and greater permeability reduction. Furthermore, although systems with porosities higher than 0.48 tend to have a relatively high clogged fraction of throats, they undergo lower permeability reduction. It was also observed that within the studied pore systems, injection of fine particles larger than 7 μm into systems with aspect ratios higher than 2.5, results in a lower fraction of clogged throats. Additionally, for the studied pore networks,< 7 μm fine particles injected into porous media with a large pore body (> 66 μm) and throat (> 22 μm) radii tended to result in larger clogging zones and a greater critical throat size of clogging.

Optimal Sensor Deployment for Parameter Estimation Precision by Integrating Bayesian Networks in Wet-Grinding Systems

Accurately and efficiently determining a system’s physical variables is crucial for precise product-quality control. This study proposes a novel method for optimal sensor deployment to increase the accuracy of sensing data for physical variables and ensure the timely detection of the product’s particle size in a wet-grinding system. This approach involves three steps. First, a Bayesian network (BN) is designed to model the cause–effect relationship between the physical variables by applying the path model. The detectability is determined to confirm that the mean shifts of all the physical variables are identifiable using sensor sets in the wet-grinding system. Second, the sensing location of accelerometers mounted on the chamber shell is determined according to the coupled computational fluid dynamics–discrete element method simulations. Third, the shuffled frog leaping algorithm is developed by combining the BN to minimize the maximum data output deviation index among all sensor sets and sensory costs; this is achieved under the constraints of the mean shift detectability, achieving optimum sensor allocation. Subsequently, a case study is performed on a zirconia powder production process to demonstrate that the proposed approach minimizes the requirements of the data output deviation index, sensory costs, and detectability. The proposed approach is systematic and universal; it can be integrated into monitor architecture for parameter estimation in other complex production systems.

Exploring the role of nasal hair in inhaled airflow and coarse dust particle dynamics in a nasal cavity: A CFD-DEM study

This study presents a novel coupled computational fluid dynamics-discrete element method (CFD-DEM) model for simulating airflow and inhaled particle dynamics in the nasal cavity, considering the fluid-structure interactions between nasal hair and airflow, which are often overlooked in existing CFD simulations. The CFD-DEM model, based on a virtual nasal cavity geometry, represents nasal hairs as flexible fibers implanted on the inner wall of the nasal cavity. Inhaled air-particle transport dynamics were simulated in the presence of nasal hairs with three different diameters (40, 95, and 120 μm), and the results were compared with simulations without nasal hairs. Polydisperse particles with diameters ranging from 5 to 15 μm, aligning with global coarse dust statistics, were inhaled at flow rates between 216 mL/s and 630 mL/s, representing human nose breathing conditions from rest to exercise. The CFD-DEM simulation results indicate that the differences in deposition fraction predictions between cases with and without nasal hairs exceed 20% for particle size ranges corresponding to impaction parameter values between 3E+3 and 2E+4 μm2cm3/s. This emphasizes the importance of accounting for nasal hair interactions in accurately simulating inhaled particle transport dynamics within the nasal cavity. Thinner nasal hairs, more flexible than thicker ones, lead to more significant deformation and allow more particles to penetrate the nasal vestibule without being trapped. Additionally, thinner hairs occupy a smaller cross-section area in the nasal vestibule, resulting in lower filtration capability due to decreased particle deposition from interception and inertial impaction. Thicker nasal hairs trap more coarse dust particles (> 5 μm) effectively than thinner nasal hairs. Moreover, as the nasal hair diameter increases, particle deposition on the nasal cavity wall decreases. Nasal hairs demonstrate higher efficiency in trapping smaller particles. In conclusion, the CFD-DEM model, capable of modeling nasal hair motion, can serve as a next-generation in silico tool for investigating biofluid dynamics in the nasal cavity.

Numerical study of the mixing characteristics in an air swirling fluidized bed with monodisperse and multi‐sized particles

AbstractPowder mixers are used in many industries. In the present work, a new type of air swirling mixer was designed and optimized with eight horizontally arranged inlet pipes at the tangential inlet angle of 35°. The mixing of multi‐sized spherical particles (2.0, 3.0, 4.0, and 5.0 mm) was numerically investigated in the air swirling mixer by coupled computational fluid dynamics–discrete element method. The numerical results showed that multi‐sized particles achieved comparable mixing performance to monodisperse particles. The Lacey index for multi‐sized particles increased initially, and then reached a maximum value at 0.824. The upward velocity of the particles, , increased initially, and then decreased to zero along the bed height. The maximum value of occurred at a height of 40 mm. Particle radial velocity was larger near the wall than at the mixer tube centre area. The smallest particles aggregated in three layers. The collision number of the particles reached a maximum at bed height of 120 mm, which was consistent with the position of the maximum stress of the particles against the tube wall.

CFD-DEM Evaluation of the Clustering Behavior in a Riser-the Effect of the Drag Force Model.

Riser reactors are frequently applied in catalytic processes involving rapid catalyst deactivation. Typically heterogeneous flow structures prevail because of the clustering of particles, which impacts the quality of the gas-solid contact. This phenomenon results as a competition between fluid-particle interaction (i.e., drag) and particle-particle interaction (i.e., collisions). In this study, five drag force correlations were used in a combined computational fluid dynamics-discrete element method Immersed Boundary Model to predict the clustering. The simulation results were compared with experimental data obtained from a pseudo-2D riser in the fast fluidization regime. The clusters were detected on the basis of a core-wake approach using constant thresholds. Although good predictions for the global (solids volume fraction and mass flux) variables and cluster (spatial distribution, size, and number of clusters) variables were obtained with two of the approaches in most of the simulations, all the correlations show significant deviations in the onset of a pneumatic transport regime. However, the correlations of Felice (Int. J. Multiphase Flow1994, 20, 153-159) and Tang et al. [AIChE J.2015, 61 ( (2), ), 688-698] show the closest correspondence for the time-averaged quantities and the clustering behavior in the fast fluidization regime.

Method for calculating pressure losses in the pipelines of slurry shield tunneling based on coupled simulation of computational fluid dynamics and discrete element method

AbstractHydraulic mucking/transport or slurry pipelining are widely used in dredging, trenching, (deep sea) mining, tunnel boring, and many other applications. Slurry pipelining during slurry shield tunneling is a classic instance of complex hydraulic mucking systems, which is characterized by the complex rheological behavior of the slurry and the inclusion of large and irregular particles. These characteristics make it difficult to estimate the pressure losses along slurry pipelines, compared to other hydraulic mucking systems. This study established a powerful method for predicting the pressure losses in long‐distance slurry pipelining of slurry shield tunneling based on computational fluid dynamics–discrete element method (CFD‐DEM)‐coupled simulations. Rheological tests were carried out to provide reliable slurry flow parameters for CFD calculations. Irregular pebbles with different sizes were digitally scanned using 3D scanning technology, and the scanned models were applied to the DEM. This method was successfully applied to a slurry shield tunnel project in Beijing, China. The mechanical properties of the fluid phase and particle phase were revealed by modeling a typical slurry pipeline. A comparison of the pressure losses along slurry pipelines was made between the proposed method and field data, indicating the validity of the established method. The simulation results indicate that when the slurry flows through the elbow, a secondary flow will be formed due to centrifugal force. Pebbles of different sizes show different motion responses under the combined action of gravity and slurry coupling force. The turbulent flow of particles will increase the frictional pressure losses in the elbow area, compared to the straight section. This work provides a valuable reference for the layout of the slurry circulation system of similar projects.

Pd/oCNT Monolithic Catalysts for Continuous-Flow Selective Hydrogenation of Cinnamaldehyde

Chemical engineering optimization from a batch process to continuous flow in liquid-phase hydrogenation brings a significant improvement in efficiency. However, its further application is limited due to the severe pressure drop and tube blockage problems in a powder-form catalyst fixed-bed reactor, especially for nanocarbon-supported catalysts. In this work, spherical monoliths containing oxygenated carbon nanotube (oCNT)-supported Pd nanoparticles (ca. average size of 2 mm) are fabricated via an in situ gelation method and applied for cinnamaldehyde (CAL) selective hydrogenation in a continuous-flow system. The simulated results by the computational fluid dynamics–discrete element method (CFD–DEM) coupled method show that the pressure drop of the monolith catalyst bed is maintained within 0.4 Pa. The Pd/oCNT monolithic catalyst exhibits excellent CAL conversion of 85.8% and hydrocinnamaldehyde (HCAL) selectivity of 93.5% within a high weight hourly space velocity (WHSV) of 0.012 s–1 at mild reaction conditions (30 °C, 3 bar). The catalyst maintains robust catalytic activity and HCAL selectivity (>93%) under varied reaction temperatures (30/60 °C), H2 partial pressures (3–10 bar), and WHSVs (0.012–0.184 s–1) and a stable reaction activity for more than 60 h time on stream, revealing the possibility in industrial hydrogenation reactions. The catalytic activity of the monolithic catalyst is determined by the surface properties of the carbon nanotubes and the chemical interactions between Pd nanoparticles and supports. The oxygenated functional groups and surface defects on oCNTs are beneficial for strong chemical interaction with Pd species, which forms abundant electron-deficient Pdδ+ species to facilitate C═C hydrogenation. This study puts forward insights into and perspectives for selective hydrogenation reactions in both electronic structure tuning of the active phase at the atomic scale and fabrication of monolithic catalysts at the macroscopic scale.

Numerical and experimental investigation of flow and heat transfer in a fixed bed of non‐spherical grains using the DEM‐CFD method

AbstractFixed‐bed drying of grains is a widely used method for determining temperature and humidity changes and pressure drop characteristics during aeration. In this study, an accurate particle‐resolved computational fluid dynamics (CFD) numerical model was developed to investigate the flow and heat transfer in fixed beds of soybean, wheat, and maize grains. A randomly filled non‐spherical grain fixed bed structure was generated using the discrete element method (DEM), and the contact areas between the packed particles are automated. The distribution of grain particles near the wall surface was approximately circular, and the circle became more regular with increase grain sphericity. Compared with the fixed beds of soybean and maize, there was no significant stratification in the fixed beds of wheat, and the difference between the peaks and troughs of porosity oscillations was smaller. Detailed particle‐resolved CFD simulations of the flow and heat transfer in fixed beds with different grains were performed. The results showed that the pressure drop results of the DEM–CFD simulation of different grain shapes were in good agreement with the Nemec–Levec equation and experimental results. The velocity and temperature distribution in the fixed bed have obvious non‐uniform distribution characteristics, which are more visible in the maize pile. Regions with high porosity have a higher average velocity, and the temperature near the wall is higher than that at the center when the heat transfer is unbalanced. The DEM‐CFD model includes the heat conduction process between the fluid and solid phases, which is consistent with the experimental temperature results.Practical ApplicationsIn this work, an accurate particle‐resolved computational fluid dynamics numerical model was developed to investigate the flow and heat transfer in fixed beds of soybean, wheat, and maize grains. The randomly filled non‐spherical grain fixed bed structure is generated by the discrete element method (DEM), and the contact areas between the packed particles are automated treated. The pressure drop and heat transfer processes of different grains were measured using the fixed bed drying experimental platform. The results show that the pressure drop results of DEM–CFD simulation of different grain shapes are in good agreement with Nemec–Levec equation results and experimental results. The DEM‐CFD model includes the heat conduction process between fluid and solid phases, which is in close agreement with the experimental temperature results.

Semi-resolved CFD-DEM coupling model for submerged granular collapse

Submerged granular collapse involves strong interaction between fluid and particles, while the widely applied unresolved computational fluid dynamics-discrete element method (CFD-DEM) coupling model cannot accurately simulate the interaction when the particle-grid size ratio is >1/3. Herein, a semi-resolved CFD-DEM coupling model is employed to eliminate the size ratio limitation. This model approximates the ambient fluid variables required by the hydraulic force calculation within an expanded dependent domain, and allocates the particle volume and reacting drag force to fluid within an expanded influential domain. The performance of the semi-resolved model in simulating a submerged granular collapse is studied by comparing the numerical results with the experimental data in detail. Results show that the simulated deposit morphologies, including the surface, residual height, and runout distance of the granular columns, well agree with the measured data. Moreover, since the limitation on the size ratio is eliminated, the numerical simulations well reproduce the details of the collapse-induced fluid flows observed in experiments, especially the evolution of the shear vortex above the interface between fluid and particles.

Numerical research on the particle transport and deposition in the impingement-film cooling passage

With the aim of exploring the particle transport and deposition characteristics in the internal cooling channel of turbine blades, the computational fluid dynamics-discrete element method is used to implement the numerical simulation of particle transport and deposition in the impingement-film cooling passage. First, the unsteady development process of the particle transport and deposition with the increase in injection particle mass is obtained. Then, the effect of jets Reynolds number, particle Stokes number, and initial particle volume fraction on the particle deposition characteristics is presented. Finally, the particle deposition mechanism in the impingement-film cooling passage of turbine blades is revealed. The results show that the conical-shape particle deposition layer is formed at the impingement stagnation point region and the banded-shape particle deposition layer is formed between adjacent impingement holes. The cooling gas carrying particles is injected from the impact hole and subjected to the fluid shear force. Then, the cooling gas carrying particles gradually developed into the conical-shape free jets. In addition, the symmetrical vortex structure is formed due to the collision of the adjacent jets. Therefore, the particle deposition layer is formed on the impingement target surface, which is caused by the energy attenuation due to the continuous collision of the particle with the particle and the particle with the wall. The increase in the jets Reynolds number inhibits the particle deposition behavior, and the increase in the Stokes number accelerates the particle deposition behavior.

An algorithm combining sedimentation experiments for pipe erosion investigation

Hydraulic fracturing is an essential technology for continuously developing non-renewable energy, such as oil and gas. The erosion of solid-liquid two-phase flow in hydraulic fracturing is a theoretical problem that needs to be solved urgently. In the current computational fluid dynamics-discrete element method (CFD-DEM) research, we present calculation methods for the collision restitution coefficients of quartz particle in Newtonian fluids (1 mPa s) and non-Newtonian fluids (10 mPa s and 20 mPa s). The influence of power-law fluid is considered in the algorithm, and the problem of particle penetration in the CFD-DEM method is optimized. These experimentally obtained collision restitution coefficients are incorporated into the optimized CFD-DEM method to consider the influence of fluid viscous forces on particle collisions. The accuracy of the numerical simulation method in this paper is verified by particle settlement and erosion experiments. The elbow erosion experiment is then used to validate the correctness of the erosion simulation. Finally, the erosion behavior of the fracturing pipe (elbow and tee junction) under different conditions is analyzed.

Simulation of gas-solids heat transfer in cyclone pyrolyzer using CFD-DEM model

Fast heat transfer in the pyrolyzer can increase the yield of pyrolysis gas and tar, and improve the quality of tar. Compared with the downer pyrolyzer, the cyclone pyrolyzer can simultaneously achieve high solids holdup and violent turbulence, and correspondingly faster heat transfer. In this work, the heat transfer behavior in the cyclone pyrolyzer is specifically studied using the computational fluid dynamics-discrete element method. The simulation results reveal that the gas-solids heat convection contributes mainly to the heat transfer process, and the heat radiation and conduction are relatively small and almost negligible, respectively. Compared with the downer pyrolyzer under the same operating conditions, the heating rate is significantly increased in the cyclone pyrolyzer. By analyzing the flow characteristics in the cyclone pyrolyzer, it is found that the region of high convective heat transfer rate coincides with that of natural cyclone length. Additionally, the final coal temperature increases with the increase of gas velocity and exists a maximum value. These results can offer some qualitative understanding of the heat transfer behavior in the cyclone pyrolyzer.

Investigating the inflow into a granular bed using a locally resolved method

Discrete Element Method – Computational Fluid Dynamics (DEM/CFD) simulations of industrial-scale granular systems employ spatial averaging (porous media approach) for the fluid-particle interaction in the whole domain, which can lead to poor accuracy, for instance at flow inlets, as local particle bulk morphology is not resolved. This paper presents an approach where the interstitial flow in crucial areas with large gradients can be resolved locally in an otherwise unresolved domain, so that a mixed resolved-unresolved method is realized.As a generic example to show the feasibility and performance of the new approach, the inflow of ambient air into a flat-bottom hopper through a narrow orifice is investigated. In an experimental setup, the vertical profile of the pressure decay through the inlet and across the packing is chosen for comparison with respective simulations. Results obtained with the conventional porous media method and the locally resolved approach are compared to these experiments for varying volume flow rates and for two different particle shapes. Spheres of different size as well as dodecahedrons are examined.It is found that although averaging methods already provide good approximations, the locally resolved method can improve the result especially when conventional drag laws are not applicable due to wall effects or if large velocity gradients exist.

Numerical investigation of subcritical and supercritical carbon dioxide fluidized beds using two fluid model and discrete element method

Fluidization state of ambient, subcritical and supercritical carbon dioxide (CO2) fluid fluidized beds are simulated using Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) and Two-Fluid Model (TFM) combined with Low Density Ratio-Kinetic Theory of Granular Flow (LDR-KTGF). Quantitative and qualitative analysis were executed between TFM and CFD-DEM simulation results. Fluidization process using two methods coincides with predictions of stability function and different criteria for distinguishing from particulate and aggregative fluidizations. A transitional fluidization with the wave-like and chunk-like flows occurs in subcritical CO2 fluid fluidized bed, and the bubble-like and particle aggregative-like flows are observed in ambient and supercritical states, respectively. The discrepancies in volume fractions and velocities obtained using TFM and CFD-DEM approaches were small, while the predicted turbulent kinetic parameters and bubble-like kinetic energy show sensitivity to the turbulence model. Statistical analysis of the turbulent normal Reynolds stresses indicated an anisotropic flow of particles.

Multiphysics coupling investigation of interphase heat transfer in gas-particle coaxial-jet swirling flow via CFD-DEM-CHT

The swirling particulate flows with heat transfer are widely encountered in the industry, yet the internal multiphysics coupling characteristics resulting from fluid, particle, and structure interactions are not well-understood. In present employment, a coupled method of computational fluid dynamics-discrete element method and conjugated heat transfer is constructed to provide insights into the thermal analysis in the industrial-scale annular pipe. The heat transfer behaviors between gas-pipe wall, gas-particle, particle-particle and particle-pipe walls are taken into account for the gas-particle coaxial-jet swirling flow. After verifying the mathematical model, the heat and momentum transfer behavior is analyzed, followed by a comprehensive exploration of fluid hydrodynamics, heat transfer characteristics, and particle properties under diverse swirler geometries. The results demonstrate that the presence of the swirler reinforces the forced convection between the jet and the high-temperature pipe wall. The heat exchange performance between the jet and the Wallcp-ann-cas enhances with the increase of vane angle and diameter of the swirler but decreases with the increase of swirler height. The impact of the swirler installing position on the thermophysical field can be neglected. An excessive number of swirler vanes adversely impacts the heat transfer process between the gas phase and pipe walls. The particle temperature increases with decreasing height, while the particle Nusselt number increases and then decreases with the decrease in height.

CFD-DEM simulation of fluorination reaction in fluidized beds with local grid and time refinement method

The gas-solid reaction process with wide particle size distribution is extensively used in the chemical engineering field, especially the particle reacts with the gas gradually, such as fluorination reactions in fluidized beds. When the computational fluid dynamics-discrete element method (CFD-DEM) is used for the coupling simulation of multiphase and polydisperse particle reaction system, the grid size directly affects the accuracy of flow field information and simulation of chemical reaction. Furthermore, particle calculation time step will directly affect the efficiency of coupling calculation. In this work, a local grid and time step refinement method is proposed to simulate multiphase and polydisperse particle fluidization reaction system. In this method, the refined DEM grids are automatically generated in the computational domain around the fine particles, and the detailed fluid phase information is obtained with the interpolation algorithm. In the two-phase coupling process, particles are divided into different groups based on physical properties, each group has its own independent time step. The multistage conical-cylindrical spouted bed is proposed for the fluorination reaction process; the operating gas velocity range of the polydisperse particle system is extended by the new design while the particle size distribution changes with the gas-solid reaction process. It is demonstrated that the local grid and time step refinement method can improve the accuracy and efficiency of the traditional CFD-DEM method in the reaction process simulation, which describes a polydisperse particle system with wide particle size distribution. Aimed at improving the simulation accuracy and efficiency, this paper will be helpful for simulating the particle reaction process in the gas-solid fluidized bed and beneficial for the development of the CFD-DEM method.