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This paper provides a review on the flow of free-flowing coarse particles inside silos. Basic principles and elementary mechanisms involved in gravity flow of granular materials are ...discussed. The main focus is put on flow patterns, stress distribution, velocity profiles, mass flowrate, Residence Time Distribution (RTD) and segregation inside the silo. A summary of empirical correlations as well as a synthesis of more physical and mechanistic models related to these aspects are presented. Computational and numerical methods used to describe the granular flow of particles will be discussed in a separate paper.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Approximately
75
%
of the raw material and
50
%
of the products in the chemical industry are granular materials. The discrete element method (DEM) provides detailed insights of phenomena at particle ...scale, and it is therefore often used for modeling granular materials. However, because DEM tracks the motion and contact of individual particles separately, its computational cost increases nonlinearly
O
(
n
p
log
(
n
p
)
)
–
O
(
n
p
2
)
(depending on the algorithm) with the number of particles (
n
p
). In this article, we introduce a new open-source parallel DEM software with load balancing: Lethe-DEM. Lethe-DEM, a module of Lethe, consists of solvers for two-dimensional and three-dimensional DEM simulations. Load balancing allows Lethe-DEM to significantly increase the parallel efficiency by
≈
25
–
70
%
depending on the granular simulation. We explain the fundamental modules of Lethe-DEM, its software architecture, and the governing equations. Furthermore, we verify Lethe-DEM with several tests including analytical solutions and comparison with other software. Comparisons with experiments in a flat-bottomed silo, wedge-shaped silo, and rotating drum validate Lethe-DEM. We investigate the strong and weak scaling of Lethe-DEM with
1
≤
n
c
≤
192
and
32
≤
n
c
≤
320
processes, respectively, with and without load balancing. The strong-scaling analysis is performed on the wedge-shaped silo and rotating drum simulations, while for the weak-scaling analysis, we use a dam-break simulation. The best scalability of Lethe-DEM is obtained in the range of
5000
≤
n
p
/
n
c
≤
15
,
000
. Finally, we demonstrate that large-scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional cylindrical silo with
n
p
=
4.3
×
10
6
on 320 cores.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In this research, we investigate the influence of a load-balancing strategy and parametrization on the speed-up of discrete element method simulations using Lethe-DEM. Lethe-DEM is an open-source DEM ...code which uses a cell-based load-balancing strategy. We compare the computational performance of different cell-weighing strategies based on the number of particles per cell (linear and quadratic). We observe two minimums for particle to cell weights (at 3, 40 for quadratic, and 15, 50 for linear) in both linear and quadratic strategies. The first and second minimums are attributed to the suitable distribution of cell-based and particle-based functions, respectively. We use four benchmark simulations (packing, rotating drum, silo, and V blender) to investigate the computational performances of different load-balancing schemes (namely, single-step, frequent and dynamic). These benchmarks are chosen to demonstrate different scenarios that may occur in a DEM simulation. In a large-scale rotating drum simulation, which shows the systems in which particles occupy a constant region after reaching steady-state, single-step load-balancing shows the best performance. In a silo and V blender, where particles move in one direction or have a reciprocating motion, frequent and dynamic schemes are preferred. We propose an automatic load-balancing scheme (dynamic) that finds the best load-balancing steps according to the imbalance of computational load between the processes. Furthermore, we show the high computational performance of Lethe-DEM in the simulation of the packing of 108 particles on 4800 processes. We show that simulations with optimum load-balancing need ≈40% less time compared to the simulations with no load-balancing.
High-order Computational Fluid Dynamics (CFD) methods have the potential to deliver higher accuracy at lower computational cost than conventional second-order methods. In this work, we introduce ...Lethe, an object-oriented, open-source, high-order (space and time) CFD software which leverages the well-established deal.II library. Lethe solves incompressible flow problems on 2D and 3D unstructured quad and hex meshes and allows dynamic mesh adaptation. It is parallel and it is adapted to the solution of large problems (>108 degrees of freedom) on distributed computer architectures. We illustrate some of its fundamental capacities through two benchmarks: a manufactured solution and the DNS of Taylor–Green vortices at Re=1600.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
CFD-DEM is used to simulate solid–fluid systems. DEM models the motion of discrete particles while CFD models the dynamics of the fluid phase. Coupling both necessitates the calculation of the void ...fraction and the solid–fluid forces resulting in a computationally expensive method. Additionally, evaluating volume-averaged quantities locally restricts particle to cell size ratios limiting the accuracy of the CFD. To mitigate these limitations, we develop a unified finite element CFD-DEM solver which integrates the CFD and DEM solvers into a single software resulting in faster and cheaper coupling between the solvers. It supports dynamically load-balanced parallelization. This allows for more efficient simulations as load balancing ensures the even distribution of workloads among processors; thus, exploiting available resources efficiently. Our solver supports high order schemes; thus, allowing the use of larger elements enhancing the validity and stability of the void fraction schemes while achieving better accuracy. We verify and validate our CFD-DEM solver with a large array of test cases: particle sedimentation, a fluidized bed, the Rayleigh Taylor instability, and a spouted bed.
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IJS, KILJ, NUK, PNG, UL, UM
In this research, granular mixing in vertical ribbon mixers was studied by means of discrete element method (DEM) simulations. Time‐averaged velocity distributions, granular mixing, mean square ...displacement of tracer particles, diffusion coefficients, and Peclet number in axial and azimuthal directions were used to find the flow pattern of particles and the dominant mixing mechanisms. Strong azimuthal motion of particles was observed, and it was found that by decreasing the height in the mixer, this azimuthal motion becomes stronger. The effects of rotating speed, fill level, and filling method were studied on the quality of mixing, where the quality of mixing was assessed using relative SD mixing index. It was found that by increasing the rotation speed from ωs = 60 rpm‐120 rpm, the mixing quality improves in a linear trend. Decreasing the fill level from 12 cm‐11 cm did not change the mixing quality, while with further decrease of the fill level to 10 cm, the mixing quality was improved. The mixing quality was also much better when the powder was inserted side‐to‐side instead of in axial layers.
Mixing dynamic, time‐averaged granular temperature, and velocity distribution in a vertical ribbon mixer.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•CFD-DEM formulation, including heat and mass transfer and long-range forces is described.•Implementation of CFD-DEM in simulation of different processes is discussed.•Different applications, ...including drying, coating, mixing combustion, gasification and etc. are discussed.
With increasing the computational resources, the number of publications about coupled computational fluid dynamics – discrete element method is in the rise in the recent years. This technique is very useful, especially in simulation of fluid-solid flows in process engineering. This paper provides an introduction to CFD-DEM modeling in process engineering systems, including heat and mass transfer and long range forces, and reviews the major researches in simulation of two-phase processes such as drying, coating, granulation, crystallization, chemical reactions (including combustion, gasification and pyrolysis) and mixing. Details of implementing unresolved CFD-DEM in these applications are explained in details and major assumptions and findings are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•Process Intensification (PI) refers to innovative reactor design.•PI accelerates the commercialization of CO2 capture and utilization technologies.•We review PI for popular CO2 capture technologies ...(e.g. rotating packed beds).•We review PI for catalytic, electrochemical, biological and plasma CO2 utilization.•We present limitations and perspectives for each capture and utilization technology.
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Carbon capture and utilization technologies require research and development to be implemented commercially. Process intensification (PI) technologies will help reduce the cost gap between sustainable technologies exploiting CO2 and traditional processes. In this manuscript, we present the application of the most promising PI technologies for carbon capture and conversion, their limitations, and research directions to overcome technical and economic challenges. We review different carbon capture technologies (post-combustion, pre-combustion and oxy-fuel), with a focus on rotating packed bed (RPB) and membranes being the most common, including the experimental and modeling methods used to study these technologies and their limitations. Additionally, we discuss other PI separation technologies that can be implemented for carbon capture. Among carbon utilization technologies, we present advances and future research directions of PI applied to catalytic electrochemical and biological processes, and plasma technologies. Computer-aided modeling of PI technologies provide an inexpensive approach to maximize yield before experimental testing and scale-up.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The volume‐averaged Navier‐Stokes equations are used to study fluid flow in the presence of fixed or moving solids such as packed or fluidized beds. We develop a high‐order finite element solver ...using both forms A and B of these equations. We introduce tailored stabilization techniques to prevent oscillations in regions of sharp gradients, to relax the Ladyzhenskaya–Babuska–Brezzi inf‐sup condition, and to enhance the local mass conservation and the robustness of the formulation. We calculate the void fraction using the particle centroid method. Using different drag models, we calculate the drag force exerted by the solids on the fluid. We implement the method of manufactured solution to verify our solver. We demonstrate that the model preserves the order of convergence of the underlying finite element discretization. Finally, we simulate gas flow through a randomly packed bed and study the pressure drop and mass conservation properties to validate our model.
We develop an arbitrary order finite element volume average Navier‐Stokes solver that is stabilized with streamline upwind and pressure–stabilizing Petrov–Galerkin techniques and grad div stabilization. The solver is robust, globally mass conservative and supports both models A and B of the equations. Three verification cases with increasing complexity are developed using the method of manufactured solution to verify the solver while a packed bed test case is simulated to validate the solver.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Drag force models are one of the most important factors that can affect TFM and CFD-DEM simulation results of two-phase systems. This article investigates the accuracies, implementation issues and ...limitations of the majority of the drag models for spherical, non-spherical and systems with size distribution and evaluates their performance in various simulations. Around 1888 data points were collected from 19 different sources to evaluate the drag force closures on mono-dispersed spherical particles. The Reynolds number and fluid volume fraction ranges were between 0.01 and 10,000 and between 0.33 and 1, respectively. In addition, 776 data points were collected from seven different sources to evaluate the drag force closures on poly-dispersed spherical particles. The Reynolds numbers were between 0.01 and 500, fluid volume fractions between 0.33 and 0.9, and diameter ratios up to 10. A comprehensive discussion on the accuracy and application of these models is given in the article.
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