Study of the filter cake formed due to the sedimentation of monodispersed and bidispersed particles using discrete element method–computational fluid dynamics simulations

This study aims to investigate the sedimentation and the consolidation of the packed bed/cake formed due to the monodispersed and bidispersed particles under different flow conditions. Mutual interactions between the bidispersed particles and the liquid are considered by using a polydispersed drag model. The attractive force is considered by using the JKR model. Sensitivity of the void fraction of a sedimented packed bed/cake due to particle–particle interaction parameters is studied. Furthermore, the effect of the fluid flow is analyzed by performing the simulations in two stages. In the first stage, packed bed/cake is formed by the sedimentation of the particles in the absence of the fluid forces and in the second stage flow through the packed bed/cake is simulated by using the CFD coupled with the discrete element method. Based on the simulations, correlations between the sedimented and the consolidated void fractions are developed. © 2019 American Institute of Chemical Engineers AIChE J, 65: 1294–1303, 2019     

CFD modeling of multiphase flow distribution in catalytic packed bed reactors: scale down issues

Flow maldistribution in either a bench-scale or commercial scale packed bed is often responsible for the failure of the scale down unit to mimic the performance of the large reactor. The modeling of multiphase flow in a bench-scale unit is needed for proper interpretation of reaction rate data obtained in such units. Understanding the mechanism of flow maldistribution is the first step to avoiding it. In order to achieve this objective, computational fluid dynamic (CFD) simulations of multiphase flow under steady state and unsteady state conditions in bench-scale cylindrical and rectangular packed beds are presented for the first time. The porosity distribution in packed beds is implemented into CFD simulation by pseudo-randomly assigned cell porosity values within certain constraints. The flow simulation results provide valuable information on velocity, pressure, and phase holdup distribution.     

Workflow for computational fluid dynamics modeling of fixed-bed reactors packed with metal foam pellets: Hydrodynamics

In recent years, the catalyst pellets made of open-cell metallic foams have been identified as a promising alternative in fixed-bed reactors. A reliable modeling tool is necessary to investigate the suitability of different foam properties and the shapes of foam pellets. In this article, a workflow for a detailed computational fluid dynamics (CFD) model is presented, which aims to study the flow characteristics in the slender packed beds made of metal foam pellets. The CFD model accounts for the actual random packing structure and the fluid flow throughout the interstitial regions is fully resolved, whereas flow through the porous foam pellets is represented by the closure equations for the porous media model. The bed structure is generated using rigid body dynamics (RBD) and the influence of the catalyst loading method is also considered. The mean bed voidage and the pressure drop predicted by the simulations show good agreement with the experimental data.     

A CFD model for predicting the heat transfer in the industrial scale packed bed

Compared to the traditional lumped-parameter model,computational fluid dynamics (CFD) attracted more attentions due to facilitating more accurate reactor design and optimization methods when analyzing the heat transfer in the industrial packed bed.Here,a model was developed based on the CFD theory,in which the heterogeneous fluid flow was resolved by considering the oscillatory behavior of voidage and the effective fluid viscosity.The energy transports in packed bed were calculated by the convection and diffusion incorporated with gaseous dispersion in fluid and the contacting thermal conductivity of packed particles in solids.The heat transfer coefficient between fluid and wall was evaluated by considering the turbulence due to the packed particles adjacent to the wall.Thus,the heat transfer in packed bed can be predicted without using any adjustable semi-empirical effective thermal conductivity coefficient.The experimental results from the literature were employed to validate this model.     

Performance of stress-transport models in the prediction of particle-to-fluid heat transfer in packed beds

Computational fluid dynamics (CFD) as a simulation tool allows obtaining a more complete view of the fluid flow and heat transfer mechanisms in packed bed reactors, through the resolution of 3D Reynolds averaged transport equations, together with a turbulence model when needed. This tool allows obtaining mean velocity and temperature values as well as their fluctuations at any point of the bed. An important problem when a CFD modeling is performed for turbulent flow in a packed bed reactor is to decide which turbulence model is the most accurate for this situation. Turbulence models based on the assumption of a scalar eddy viscosity for computing the turbulence stresses, so-called eddy viscosity models (EVM), seem insufficient in this case due to the big flow complexity. The use of models based on transport equations for the turbulence stresses, so-called second order closure modeling or Reynolds stress modeling (RSM), could be a better option in this case, because these models capture more of the involved physics in this kind of flow.To gain insight into this subject, a comparison between the performance in flow and heat transfer estimation of RSM and EVM turbulence models was conducted in a packed bed by solving the 3D Reynolds averaged momentum and energy equations. Several setups were defined and then computed. Thus, the numerical pressure drop, velocity, and thermal fields within the bed were obtained. In order to judge the capabilities of these turbulence models, the Nusselt number (Nu) was computed from numerical data as well as the pressure drop. Then, they were compared with commonly used correlations for parameter estimations in packed bed reactors. The numerical results obtained show that RSM give similar results as EVM for the cases checked, but with a considerably larger computational effort. This fact suggests that for this application, even though the RSM goes further into the flow physics, this does not lead to a relevant improvement in parameter estimation when compared to the performance of EVM models used.     

Co‐current descending two‐phase flows in inclined packed beds: Experiments versus simulations

The effect of inclination angle of a packed bed on its corresponding gas–liquid flow segregation and liquid saturation spatial distribution was measured in co‐current descending gas–liquid flows for varying inclinations and fluid velocities, and simulated using a two‐phase Eulerian computational fluid dynamics framework (CFD) adapted from trickle‐bed vertical configuration and based on the porous media concept. The model predictions were validated with our own experimental data obtained using electrical capacitance tomography. This preliminary attempt to forecast the hydrodynamics in inclined packed bed geometries recommends for the formulation of appropriate drag force closures which should be integrated in the CFD model for improved quantitative estimation.     

CFD modeling of single‐phase flow in a packed bed with MRI validation

Computational fluid dynamics (CFD) simulations are becoming increasingly widespread with the advent of more powerful computers and more sophisticated software. The aim of these developments is to facilitate more accurate reactor design and optimization methods compared to traditional lumped‐parameter models. However, in order for CFD to be a trusted method, it must be validated using experimental data acquired at sufficiently high spatial resolution. This article validates an in‐house CFD code by comparison with flow‐field data obtained using magnetic resonance imaging (MRI) for a packed bed with a particle‐to‐column diameter ratio of 2. Flows characterized by inlet Reynolds numbers, based on particle diameter, of 27, 55, 111, and 216 are considered. The code used employs preconditioning to directly solve for pressure in low‐velocity flow regimes. Excellent agreement was found between the MRI and CFD data with relative error between the experimentally determined and numerically predicted flow‐fields being in the range of 3–9%. © 2012 American Institute of Chemical Engineers AIChE J, 2012     

单个SMR填料的高径比及倾斜度对流场的影响

INTRODUCTION Random packing is widely used in many unit operations[1].Flow field inside a random packed bed affects the hydrodynamic and mass transfer efficiency.Study on the flow field of random packing is essential for improving hydrodynamic and mass transfer performance,while flow field investigation of single SMR packing is a foundation for random packed bed.Computational fluid dynamics (CFD)[2] may best serve for this purpose.     

小直径比固定床壁效应的CFD分析

引言固定床作为反应器、分离器、换热器等单元设备广泛应用于化工、能源、环境等许多领域。因用途的不同固定床的管径-粒径比(D/d)的范围很宽(1～1000的数量级)。大热负荷的填充床设备,如强放热的化学反应器、核反应堆的冷却壁管列等,常采用较小的管径-粒径比,以利于热量通过     

Flow dynamic in a packed bed filled with Ni-Al2O3 porous catalyst: Experimental and numerical approach

Numerical simulations and experiments have been carried out to explore the effect of particle shapes on the pressure drop and the loss factor in a packed fixed bed filled with a porous catalyst. The packed bed is presented by the Ni-Al₂O₃ catalyst of the different shapes. The commercial program ANSYS Fluent is used for the analysis; more than 20 mln cells are used for computational fluid dynamics (CFD) modeling. The catalyst particles were set as a porous medium with the viscous resistance coefficients and the inertial resistance coefficients. The comparison of the pressure drops between the experimental and simulation results show a good correlation with the divergence of results <8%. To determine the effect of the porosity properties of the medium on the numerical results, two cases of CFD modeling were realized (with taking into account the porous medium properties and without it). The discrepancy between results increases with an increasing gas flow rate.     

Numerical simulation of complex particle-fluid flows

This paper presents a numerical study of particle-fluid flow in complex three-dimensional (3D) systems by means of Combined Continuum and Discrete Method (CCDM). In the CCDM, the motion of discrete particles phase is obtained by Discrete Element Method (DEM) which applies Newton's laws of motion to every particle and the flow of continuum fluid is described by the local averaged Navier-Stokes equations that can be solved by the traditional Computational Fluid Dynamics (CFD). This method has been increasingly used worldwide, but so far its application is limited to relatively simple flow systems. In this work, the simulation is achieved by incorporating a DEM code into the commercial CFD software package Fluent that can be readily used for complex CFD problems. The applicability of this development is demonstrated in the study of the particle-fluid flow in various 3D systems including pneumatic conveying bend, cyclone separator and circulating fluidized bed. It is shown that the numerical results are, either qualitatively or quantitatively depending on the availability of experimental data for comparison, in good agreement with those measured, and can generate information leading to better understanding of the internal flow structure of these systems.     

Gas flow patterns in packed beds: A computational fluid dynamics model for wholly packed domains

This paper describes a general numerical technique for modelling three-dimensional, single-phase gas flow patterns in packed beds. Specifically, it presents a method for implementing a vectorial form of the well-known Ergun equation in a computational fluid dynamics (CFD) package. The approach is validated by comparison with independent experimental results. The general approach can be used to model flow patterns in adsorbers, catalytic reactors, etc., thus forming a useful design tool whereby packed bed configurations can be designed for minimum pressure drop while avoiding gas maldistribution.     

规整填料塔内两相流动的三维计算流体力学建模(英文)

Characterizing the complex two-phase hydrodynamics in structured packed columns requires a power- ful modeling tool. The traditional two-dimensional model exhibits limitations when one attempts to model the de- tailed two-phase flow inside the columns. The present paper presents a three-dimensional computational fluid dy- namics （CFD） model to simulate the two-phase flow in a representative unit of the column. The unit consists of an CFD calculations on column packed with Flexipak 1Y were implemented within the volume of fluid （VOF） mathe- matical framework. The CFD model was validated by comparing the calculated thickness of liquid film with the available experimental data. Special attention was given to quantitative analysis of the effects of gravity on the hy- drodynamics. Fluctuations in the liquid mass flow rate and the calculated pressure drop loss were found to be quali- tatively in agreement with the experimental observations.     

不同圆球复合无序堆积床内流动传热数值分析

圆球堆积床内孔隙分布影响其内部流场及温度场分布, 且小管径-球径比堆积床由于壁面限制, 内部孔隙率变化剧烈, 其内部流动和传热不均匀现象明显。针对D/d_p为3的圆球无序堆积床构建了3种非等直径圆球复合堆积结构:径向分层复合堆积、轴向分层复合堆积以及随机复合堆积结构, 并采用DEM-CFD方法建模计算, 从径向及整体角度分析比较不同复合堆积床内流动换热特性及其流场和温度场分布的均匀性。结果表明:孔隙率及孔隙大小分布共同影响堆积床内流场和温度场分布;相对于单一等直径圆球堆积, 采用复合堆积结构能使堆积床内部孔隙率分布更均匀, 其内部流场和温度场分布也更为均匀;对于D/d_p为3的堆积通道, 径向分层堆积结构对于提高整体流动换热性能及改善内部流动换热均匀性都有显著效果。     

移动颗粒床中高温气体渗流传热数值计算

针对移动颗粒床中物料层内的高温气体渗流传热现象 ,考虑渗流与传热的相互作用 ,采用局部非热平衡假设建立了多孔介质渗流传热物理数学模型并进行了数值计算 .研究了不同情况下床内填充多孔介质中的流速、气固温度和床层压力损失 .计算结果表明 ,高温热气对移动床颗粒料层的热渗透主要发生在渗流入口端区域 ,增大入口渗流速度以及减小床层物料下移速度将导致物料温度沿床高慢速下降 ,热渗透深度扩大 ,热渗透作用区域内的物料温度水平提高 .在热渗透作用区域 ,孔隙率对流场和压力损失有很大的影响 .研究结果对于移动颗粒床反应器的设计与运行具有一定的参考作用     

Modelling and simulation of trickle‐bed reactors using computational fluid dynamics: A state‐of‐the‐art review

Trickle‐bed reactors (TBRs), which accommodate the flow of gas and liquid phases through packed beds of catalysts, host a variety of gas–liquid–solid catalytic reactions, particularly in the petroleum/petrochemical industry. The multiphase flow hydrodynamics in TBRs are complex and directly affect the overall reactor performance in terms of reactant conversion and product yield and selectivity. Non‐ideal flow behaviours, such as flow maldistribution, channelling or partial catalyst wetting may significantly reduce the effectiveness of the reactor. However, conventional TBR modelling approaches cannot properly account for these non‐ideal behaviours owing to the complex coupling between fluid dynamics and chemical kinetics. Recent advances in the application of computational fluid dynamics (CFD) to three‐phase TBR systems have shown promise of achieving a deeper understanding of the interactions between multiphase fluid dynamics and chemical reactions. This study is intended to give a state‐of‐the‐art overview of the progress achieved in the field of CFD simulation of TBRs over the past two decades. The fundamental modelling framework of multiphase flow in TBRs, advances in important constitutive models, and the application of CFD models are discussed in detail. Directions for future research are suggested.     

CFD simulation of solids residence time distribution in a multi-compartment fluidized bed

The present work focuses on a numerical investigation of the solids residence time distribution(RTD)and the fluidized structure of a multi-compartment fluidized bed,in which the flow pattern is proved to be close to plug flow by using computational fluid dynamics(CFD)simulations.With the fluidizing gas velocity or the bed outlet height rising,the solids flow out of bed more quickly with a wider spread of residence time and a larger RTD variance(σ2).It is just the heterogeneous fluidized structure that being more prominent with the bed height increasing induces the widely non-uniform RTD.The division of the individual internal circulation into double ones improves the flow pattern to be close to plug flow.     

CFD modeling of the effect of absorbent size on absorption performance of a packed bed column

This paper reports a study on the ability of the computational fluid dynamics (CFD) modeling for analyzing the fluid flow hydrodynamics and absorption in a packed bed column. The water absorption by silica gel absorbents in an experimental packed bed was investigated, and the absorption performance of two different sizes of absorbent was studied. A series of experiments were carried out for five setups which are different in the weight ratio of the employed big to small absorbents. The CFD modeling was carried out for all five experimental setups. The predicted results show that by more replacing of the big absorbents with the small ones the water absorption increased. On the other hand, a greater pressure drop was observed as more small absorbents were used. The predicted absorption rates were compared with the measured values and on average a consistency within 11.6% was observed.     

Experimental validation of CFD simulations of a lab‐scale fluidized‐bed reactor with and without side‐gas injection

Fluidized‐bed reactors are widely used in the biofuel industry for combustion, pyrolysis, and gasification processes. In this work, a lab‐scale fluidized‐bed reactor without and with side‐gas injection and filled with 500–600 μm glass beads is simulated using the computational fluid dynamics (CFD) code Fluent 6.3, and the results are compared to experimental data obtained using pressure measurements and 3D X‐ray computed tomography. An initial grid‐dependence CFD study is carried out using 2D simulations, and it is shown that a 4‐mm grid resolution is sufficient to capture the time‐ and spatial‐averaged local gas holdup in the lab‐scale reactor. Full 3D simulations are then compared with the experimental data on 2D vertical slices through the fluidized bed. Both the experiments and CFD simulations without side‐gas injection show that in the cross section of the fluidized bed there are two large off‐center symmetric regions in which the gas holdup is larger than in the center of the fluidized bed. The 3D simulations using the Syamlal‐O'Brien and Gidaspow drag models predict well the local gas holdup variation throughout the entire fluidized bed when compared to the experimental data. In comparison, simulations with the Wen‐Yu drag model generally over predict the local gas holdup. The agreement between experiments and simulations with side‐gas injection is generally good, where the side‐gas injection simulates the immediate volatilization of biomass. However, the effect of the side‐gas injection extends further into the fluidized bed in the experiments as compared to the simulations. Overall the simulations under predict the gas dispersion rate above the side‐gas injector. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Computational fluid dynamic simulation of gas-liquid flow in rotating packed bed:A review

The rotating packed bed (RPB) has been widely used in gas-liquid flow systems as a process intensifica-tion device,exhibiting excellent mass transfer enhancement characteristics.However,the complex inter-nal structure and the high-speed rotation of the rotor in RPB bring significant challenges to study the intensification mechanism by experiment methods.In the past two decades,Computational fluid dynam-ics (CFD) has been gradually applied to simulate the hydrodynamics and mass transfer characteristics in RPB and instruct the reactor design.This article covers the development of the CFD simulation of gas-liquid flow in RPB.Firstly,the improvement of the simulation method in the aspect of mathematical mod-els,geometric models,and solving methods is introduced.Secondly,new progress of CFD simulation about hydrodynamic and mass transfer characteristics in RPB is reviewed,including pressure drop,veloc-ity distribution,flow pattern,and concentration distribution,etc.Some new phenomena such as the end effect area with the maximum turbulent have been revealed by this works.In addition,the exploration of developing new reactor structures by CFD simulation is introduced and it is proved that such new struc-tures are competitive to different applications.The defects of current research and future development directions are also discussed at last.