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This study aims to modify the standard probabilistic lattice Boltzmann methodology (LBM) cellular automata (CA) algorithm to enable a more realistic and accurate computation of the ensemble rather than individual particle trajectories that need to be updated from one time step to the next (allowing, as such, a fraction of the collection of particles in any lattice grid cell to be updated in a time step, rather than the entire collection of particles as in the standard LBM-CA algorithm leading to a better representation of the dynamic interaction between the particles and the background flow). Exploitation of the inherent parallelism of the modified LBM-CA algorithm to provide a computationally efficient scheme for computation of particle-laden flows on readily available commodity general-purpose graphics processing units (GPGPUs).

This paper presents a framework for the implementation of a LBM for the simulation of particle transport and deposition in complex flows on a GPGPU. Towards this objective, the authors have shown how to map the data structure of the LBM with a multiple-relaxation-time (MRT) collision operator and the Smagorinsky subgrid-scale turbulence model (for turbulent fluid flow simulations) coupled with a CA probabilistic method (for particle transport and deposition simulations) to a GPGPU to give a high-performance computing tool for the calculation of particle-laden flows.

A fluid-particle simulation using our LBM-MRT-CA algorithm run on a single GPGPU was 160 times as computationally efficient as the same algorithm run on a single CPU.

The method is limited by the available computational resources (e.g. GPU memory size).

A new 3D LBM-MRT-CA model was developed to simulate the particle transport and deposition in complex laminar and turbulent flows with different hydrodynamic characteristics (e.g. vortex shedding, impingement, free shear layer, turbulent boundary layer). The solid particle information is encapsulated locally at the lattice grid nodes, allowing for straightforward mapping of the datastructure onto a GPGPU enabling a massive parallel execution of the LBM-MRT-CA algorithm. The new particle transport algorithm was based on the local (bulk) particle density and velocity and provides more realistic results for the particle transport and deposition than the standard LBM-CA algorithm.

The purpose of this paper is to perform the computational fluid dynamics (CFD) simulation with experimental validation to investigate the particle segregation effect in abrupt and smooth shapes circulating fluidized bed (CFB) risers.

The experimental investigations were carried out in lab-scale CFB systems and the CFD simulations were performed by using commercial software BARRACUDA. Special attention was paid to investigate the gas-particle flow behavior at the top of the riser with three different superficial velocities, namely, 4, 6 and 7.7 m/s. Here, a CFD-based noble simulation approach called multi-phase particle in cell (MP-PIC) was used to investigate the effect of traditional drag models (Wen-Yu, Ergun, Wen-Yu-Ergun and Richardson-Davidson-Harrison) on particle flow characteristics in CFB riser.

Findings from the experimentations revealed that the increase in gas velocity leads to decrease the mixing index inside the riser. Moreover, the solid holdup found more in abrupt riser than smooth riser at the constant gas velocity. Despite the more experimental investigations, the findings with CFD simulations revealed that the MP-PIC approach, which was combined with different drag models could be more effective for the practical (industrial) design of CFB riser. Well agreement was found between the simulation and experimental outputs. The simulation work was compared with experimental data, which shows the good agreement (<4%).

The experimental and simulation study performed in this research study constitutes an easy-to-use with different drag coefficient. The proposed MP-PIC model is more effective for large particles fluidized bed, which can be helpful for further research on industrial gas-particle fluidized bed reactors. This study is expected to give throughout the analysis of CFB hydrodynamics with further exploration of overall fluidization.

The purpose of this paper is to extend complex-shaped discrete element method simulations from a few thousand particles to millions of particles by using parallel computing on department of defense (DoD) supercomputers and to study the mechanical response of particle assemblies composed of a large number of particles in engineering practice and laboratory tests.

Parallel algorithm is designed and implemented with advanced features such as link-block, border layer and migration layer, adaptive compute gridding technique and message passing interface (MPI) transmission of C++ objects and pointers, for high performance optimization; performance analyses are conducted across five orders of magnitude of simulation scale on multiple DoD supercomputers; and three full-scale simulations of sand pluviation, constrained collapse and particle shape effect are carried out to study mechanical response of particle assemblies.

The parallel algorithm and implementation exhibit high speedup and excellent scalability, communication time is a decreasing function of the number of compute nodes and optimal computational granularity for each simulation scale is given. Nearly 50 per cent of wall clock time is spent on rebound phenomenon at the top of particle assembly in dynamic simulation of sand gravitational pluviation. Numerous particles are necessary to capture the pattern and shape of particle assembly in collapse tests; preliminary comparison between sphere assembly and ellipsoid assembly indicates a significant influence of particle shape on kinematic, kinetic and static behavior of particle assemblies.

The high-performance parallel code enables the simulation of a wide range of dynamic and static laboratory and field tests in engineering applications that involve a large number of granular and geotechnical material grains, such as sand pluviation process, buried explosion in various soils, earth penetrator interaction with soil, influence of grain size, shape and gradation on packing density and shear strength and mechanical behavior under different gravity environments such as on the Moon and Mars.

The purpose of this study is to explore how particle shape influences the screening, including screening efficiency per unit time, and the relationship between vibration parameters and screening efficiency per unit time in discrete element method (DEM) numerical simulations.

In this paper, a three-dimensional discrete element model of vibrating screen with composite vibration form of swing and translation was proposed to simulate the screening process. In total, 11 kinds of non-spherical particles whose shapes changed in a continuous regularity gradual process were established using a multi-sphere method. In the DEM simulations, vibration parameters, including vibration frequency, vibration amplitude and stroke angle, and swing parameters, including swing frequency and swing angle, were changed to perform parametric studies.

It shows that the effect of particle shape on screening efficiency is quantitative actually. However, the trends of different shape particles’ screening efficiency per unit time are mainly consistent.

Some simple particle shapes can be expected to be explored to do screening simulation studies reasonably with modification of the simulation data in DEM numerical simulations. That may improve the computational efficiency of numerical simulations and provide guidance to the study of the screening process.

The purpose of this paper is to find the best solver for parallelizing particle methods based on solving Pressure Poisson Equation (PPE) by taking Moving Particle Semi-Implicit (MPS) method as an example because the solution for PPE is usually the most time-consuming part difficult to parallelize.

To find the best solver, the authors compare six Krylov solvers, namely, Conjugate Gradient method (CG), Scaled Conjugate Gradient method (SCG), Bi-Conjugate Gradient Stabilized (BiCGStab) method, Conjugate Gradient Squared (CGS) method with Symmetric Lanczos Algorithm (SLA) method and Incomplete Cholesky Conjugate Gradient method (ICCG) in terms of convergence, time consumption, parallel efficiency and memory consumption for the semi-implicit particle method. The MPS method is parallelized by the hybrid Open Multi-Processing (OpenMP)/Message Passing Interface (MPI) model. The dam-break flow and channel flow simulations are used to evaluate the performance of different solvers.

It is found that CG converges stably, runs fastest in the serial way, uses the least memory and has highest OpenMP parallel efficiency, but its MPI parallel efficiency is lower than SLA because SLA requires less synchronization than CG.

With all these criteria considered and weighed, the recommended parallel solver for the MPS method is CG.

The purpose of this paper is to study the complex aerosol dynamic processes by using this newly developed stochastically weighted operator splitting Monte Carlo (SWOSMC) method.

Stochastically weighted particle method and operator splitting method are coupled to formulate the SWOSMC method for the numerical simulation of particle-fluid systems undergoing the complex simultaneous processes.

This SWOSMC method is first validated by comparing its numerical simulation results of constant rate coagulation and linear rate condensation with the corresponding analytical solutions. Coagulation and nucleation cases are further studied whose results are compared with the sectional method in excellent agreement. This SWOSMC method has also demonstrated its high numerical simulation capability when used to deal with simultaneous aerosol dynamic processes including coagulation, nucleation and condensation.

There always exists conflict and tradeoffs between computational cost and accuracy for Monte Carlo-based methods for the numerical simulation of aerosol dynamics. The operator splitting method has been widely used in solving complex partial differential equations, while the stochastic-weighted particle method has been commonly used in numerical simulation of aerosol dynamics. However, the integration of these two methods has not been well investigated.

This paper aims to present a novel approach for computing particle temperatures in simulations coupling computational fluid dynamics (CFD) and discrete element method (DEM) to predict flow and heat transfer in fluidized beds of thermally thick spherical particles.

An improved lumped formulation based on Hermite-type approximations for integrals to relate surface temperature to average temperature and surface heat flux is used to overcome the limitations of classical lumped models. The model is validated through comparisons with analytical solutions for a convectively cooled sphere and experimental data for a fixed particle bed. The coupled CFD-DEM model is then applied to simulate a Geldart D bubbling fluidized bed, comparing the results to those obtained using the classical lumped model.

The validation cases demonstrate that ignoring internal thermal resistance can significantly impact the temperature in cases where the Biot number is greater than 0.1. The results for the fixed bed case clearly demonstrate that the proposed method yields significantly improved outcomes compared to the classical model. The fluidized bed results show that surface temperature can deviate considerably from the average temperature, underscoring the importance of accurately accounting for surface temperature in convective heat transfer predictions and surface processes.

The proposed approach offers a physically more consistent simulation without imposing a significant increase in computational cost. The improved lumped formulation can be easily and inexpensively integrated into a typical DEM solver workflow to predict heat transfer for spherical particles, with important implications for various industrial applications.

Bulk material-handling equipment development can be accelerated and is less expensive when testing of virtual prototypes can be adopted. However, often the complexity of the interaction between particulate material and handling equipment cannot be handled by a single computational solver. This paper aims to establish a framework for the development, verification and application of a co-simulation of discrete element method (DEM) and multibody dynamics (MBD).

The two methods have been coupled in two directions, which consists of coupling the load data on the geometry from DEM to MBD and the position data from MBD to DEM. The coupling has been validated thoroughly in several scenarios, and the stability and robustness have been investigated.

All tests clearly demonstrated that the co-simulation is successful in predicting particle–equipment interaction. Examples are provided describing the effects of a coupling that is too tight, as well as a coupling that is too loose. A guideline has been developed for achieving stable and efficient co-simulations.

This framework shows how to achieve realistic co-simulations of particulate material and equipment interaction of a dynamic nature.

The purpose of this paper is to examine several calibration techniques that have been developed to determine the discrete element method (DEM) parameters for slow and rapid unconfined flow of granular conical pile formation. This paper also aims to discuss some of the methods currently employed to scale particle properties to reduce computational resources and time to solve large DEM models.

DEM models have been calibrated against simple bench‐scale experimental results to examine the validity of selected parameters for the contact, material and mechanical models to simulate the dynamic and static behaviour of cohesionless polyethylene pellets. Methods to determine quantifiable single particle parameters such as static friction and the coefficient of restitution have been highlighted. Numerical and experimental granular pile formation has been investigated using different slumping and pouring techniques to examine the dependency of the type of flow mechanism on the DEM parameters.

The proposed methods can provide cost effective and simple techniques to determine suitable input parameters for DEM models. Rolling friction and particle shape representation has shown to have a significant influence on the bulk flow characteristics via a sensitivity analysis and needs to be accessed based on the environmental conditions.

This paper describes several effective known and novel methodologies to characterise granular materials that are needed to accurately model granular flow using the DEM to provide valuable quantitative data. For the DEM to be a viable predictive tool in industrial applications which often contain huge quantities of particles with random particle shapes and irregular properties, quick and validated techniques to “tune” DEM models are necessary.

The purpose of this paper is to obtain the combination of working parameters suitable for pulsating negative pressure shale shaker through simulation, which is conducive to efficient recovery of clean drilling fluid and relatively dry cuttings.

Shale shaker is still one of the main equipment in solid–solid and solid–liquid separation processes in drilling industry. This research is based on a new drilling fluids circulation treatment device, namely pulsating negative pressure shale shaker. In this work, a numerical study of particle flow and separation in the pulsating negative pressure shale shaker is carried out by coupling computational fluid dynamics/discrete element method (CFD-DEM). The effect of vibration parameters and negative pressure parameters are studied in terms of conveyance velocity and percent through screen.

The results show that, conveyance velocity of particle is mainly affected by vibration parameters, negative pressure in pulsating form can effectively prevent cuttings from sticking to the screen. Vibration parameters and pulsating airflow velocity peak have great influence on percent through screen, while vibration frequency and screen slope have influence on the time when the percent through screen reaches stability.

In this paper, the authors put forward a new kind of drilling waste fluid treatment equipment, and focused on the study of particle movement law. The results have important guiding significance for the selection of structural design parameters and rational use of equipment. In addition, the new device provides a new idea for solid–liquid separation method, which is one of the hot topics in current research.