Isotropic compression behavior of granular assembly with non-spherical particles by X-ray micro-computed tomography and discrete element modeling

The particle morphological properties,such as sphericity,concavity and convexity,of a granular assembly significantly affect its macroscopic and microscopic compressive behaviors under isotropic loading condition.However,limited studies on investigating the microscopic behavior of the granular assembly with real particle shapes under isotropic compression were reported.In this study,X-ray computed tomography(mCT)and discrete element modeling(DEM)were utilized to investigate isotropic compression behavior of the granular assembly with regard to the particle morphological properties,such as particle sphericity,concavity and interparticle frictions.The mCT was first used to extract the particle morphological parameters and then the DEM was utilized to numerically investigate the influences of the particle morphological properties on the isotropic compression behavior.The image reconstruction from mCT images indicated that the presented particle quantification algorithm was robust,and the presented microscopic analysis via the DEM simulation demonstrated that the particle surface concavity significantly affected the isotropic compression behavior.The observations of the particle connectivity and local void ratio distribution also provided insights into the granular assembly under isotropic compression.Results found that the particle concavity and interparticle friction influenced the most of the isotropic compression behavior of the granular assemblies.

An Innovative Coupled Common-Node Discrete Element Method-Smoothed Particle Hydrodynamics Model Developed with LS-DYNA and Its Applications

In this study,a common-node DEM-SPH coupling model based on the shared node method is proposed,and a fluid–structure coupling method using the common-node discrete element method-smoothed particle hydrodynamics(DS-SPH)method is developed using LS-DYNA software.The DEM and SPH are established on the same node to create common-node DEM-SPH particles,allowing for fluid–structure interactions.Numerical simulations of various scenarios,including water entry of a rigid sphere,dam-break propagation over wet beds,impact on an ice plate floating on water and ice accumulation on offshore structures,are conducted.The interaction between DS particles and SPH fluid and the crack generation mechanism and expansion characteristics of the ice plate under the interaction of structure and fluid are also studied.The results are compared with available data to verify the proposed coupling method.Notably,the simulation results demonstrated that controlling the cutoff pressure of internal SPH particles could effectively control particle splashing during ice crushing failure.

ON EQUATION OF DISCRETE SOLID PARTICLES' MOTION IN ARBITRARY FLOW FIELD AND ITS PROPERTIES

The forces on rigid particles moving in relation to fluid having been studied and the equation of modifications of their expressions under different flow conditions discussed, a general form of equation for discrete particles' motion in arbitrary flow field is obtained. The mathematical features of the linear form of the equation are clarified and analytical solution of the linearized equation is gotten by means of Laplace transform. According to above theoretical results, the effects of particles' properties on its motion in several typical flow field are studied, with some meaningful conclusions being reached.

A new method to simulate irregular particles by discrete element method

Granular materials are ubiquitous in nature and important in various applications such as road and railway engineering. Granular materials exhibit complicated mechanical behaviors, which are affected significantly by the irregular shape of particles. Currently, the discrete element method (DEM) has been accepted as an effective approach to investigate the mechanical behaviors of granular materials. However, there are scarce simulations based on DEM in literatures considering the irregularity of particle shape. A new method is proposed to simulate individual real particle with irregular shape using clump constituted by overlapping spheres. First, the geometric model of real particle with surface nodes and inner nodes is established through digitally processing the computerized tomography (CT) scanning data. Second, a clump consisting of spheres is generated to simulate the real particle using a minimum distance criterion. The criterion is implemented by tree optimization algorithm. Influential factors are also introduced to balance the model accuracy and computing cost. Effects of the influential factors, including the density of geometric grid and the minimum distance, on simulations are discussed. Results show that this new method is simpler and more efficient than the previous methods in terms of the model accuracy and computing cost.

Scattering and absorption characteristics of non-spherical cirrus cloud ice crystal particles in terahertz frequency band

We used discrete dipole approximation(DDA)to examine the scattering and absorption characteristics of spherical ice crystal particles.On this basis,we studied the scattering characteristics of spherical ice crystal particles at different frequencies and non-spherical ice crystal particles with different shapes,aspect ratios,and spatial orientations.The results indicate that the DDA and Mie methods yield almost the same results for spherical ice crystal particles,illustrating the superior calculation accuracy of the DDA method.Compared with the millimeter wave band,the terahertz band particles have richer scattering characteristics and can detect ice crystal particles more easily.Different frequencies,shapes,aspect ratios,and spatial orientations have specific effects on the scattering and absorption characteristics o f ice crystal particles.The results provide an important theoretical basis for the design of terahertz cloud radars and related cirrus detection methods.

Applicability of discrete element method with spherical and clumped particles for constitutive study of granular materials

Discrete element method(DEM)has been intensively used to study the constitutive behaviour of granular materials.However,to what extent a real granular material can be reproduced by virtual DEM simulations remains unclear.This study attempts to answer this question by comparing DEM simulations with typical features of experimental granular materials.Three groups of models with spherical and clumped particles are investigated from four perspectives:(i)deviatoric stress and volumetric behaviour;(ii)critical state behaviour;(iii)stress-dilatancy relationship;and(iv)the evolution of principal stress ratio against axial strain.The results demonstrate that DEM with spherical or clumped particles is capable of qualitatively describing macroscopic deviatoric stress responses,volumetric behaviour,and critical state behaviour observed in experiments for granular materials.On the other hand,some qualitative deviations between experiments and the investigated DEM simulations are also observed,in terms of the stress-dilatancy behaviour and principal stress ratio against axial strain,which are proven to be critical for constitutive modelling.The results demonstrate that DEM with spherical or clumped particles may not necessarily fully capture experimental features of granular materials even from a qualitative perspective.It is thus encouraged to thoroughly validate DEM with experiments when developing constitutive models based on DEM observations.

Distribution of non-spherical nanoparticles in turbulent flow of ventilation chamber considering fluctuating particle number density

The Reynolds-averaged general dynamic equation(RAGDE)for the nanoparticle size distribution function is derived,including the contribution to particle coagulation resulting from the fluctuating concentration.The equation together with that of a turbulent gas flow is solved numerically in the turbulent flow of a ventilation chamber with a jet on the wall based on the proposed model relating the fluctuating coagulation to the gradient of mean concentration.Some results are compared with the experimental data.The results show that the proposed model relating the fluctuating coagulation to the gradient of mean concentration is reasonable,and it is necessary to consider the contribution to coagulation resulting from the fluctuating concentration in such a flow.The changes of the particle number concentration M_(0) and the geometric mean diameter dg are more obvious in the core area of the jet,but less obvious in other areas.With the increase in the initial particle number concentration m00,the values of M_(0) and the standard deviation of the particle sizeσdecrease,but the value of d_(g) increases.The decrease in the initial particle diameter leads to the reduction of M_(0) andσand the increase in d_(g).With the increase in the Reynolds number,particles have few chances of collision,and hence the coagulation rate is reduced,leading to the increase in M_(0) andσand the decrease in d_(g).

Application of a Neural Network to Store and Compute the Optical Properties of Non-Spherical Particles

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical particles.This paper proposes a deep learning(DL)scheme in conjunction with an optical property database to achieve this goal.Deep neural network(DNN)architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters,size parameters,and refractive indices.The dataset was computed through the invariant imbedding T-matrix method.Four separate DNN architectures were created to compute the extinction efficiency factor,single-scattering albedo,asymmetry factor,and phase matrix.The criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN parameters.The numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database,which indicates that the DNN can reproduce the optical properties in the dataset with high accuracy.In addition,the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the database.Importantly,the ratio of the database size(~127 GB)to that of the DNN parameters(~20 MB)is approximately 6810,implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models.

Non-spherical particle mixing behaviors by spherical inert particles assisted in a fluidized bed

Fluidized beds are widely used in many industrial fields such as petroleum,chemical and energy.In actual industrial processes,spherical inert particles are typically added to the fluidized bed to promote fluidization of non-spherical particles.Understanding mixing behaviors of binary mixtures in a fluidized bed has specific significance for the design and optimization of related industrial processes.In this study,the computational fluid dynamic-discrete element method with the consideration of rolling friction was applied to evaluate the mixing behaviors of binary mixtures comprising spherocylindrical particles and spherical particles in a fluidized bed.The simulation results indicate that the differences between rotational particle velocities were higher than those of translational particle velocities for spherical and non-spherical particles when well mixed.Moreover,as the volume fraction of the spherocylindrical particles increases,translational and rotational granular temperatures gradually increase.In addition,the addition of the spherical particles makes the spherocylindrical particles preferably distributed in a vertical orientation.

A CFD-DEM-Wear Coupling Method for Stone Chip Resistance of Automotive Coatings with a Rigid Connection ParticleMethod for Non-Spherical Particles

The stone chip resistance performance of automotive coatings has attracted increasing attention in academic and industrial communities.Even though traditional gravelometer tests can be used to evaluate stone chip resistance of automotive coatings,such experiment-based methods suffer from poor repeatability and high cost.The main purpose of this work is to develop a CFD-DEM-wear coupling method to accurately and efficiently simulate stone chipbehaviorof automotive coatings inagravelometer test.Toachieve this end,an approach coupling an unresolved computational fluid dynamics(CFD)method and a discrete element method(DEM)are employed to account for interactions between fluids and large particles.In order to accurately describe large particles,a rigid connection particle method is proposed.In doing so,each actual non-spherical particle can be approximately described by rigidly connecting a group of non-overlapping spheres,and particle-fluid interactions are simulated based on each component sphere.An erosion wear model is used to calculate the impact damage of coatings based on particlecoating interactions.Single spherical particle tests are performed to demonstrate the feasibility of the proposed rigid connection particle method under various air pressure conditions.Then,the developed CFD-DEM-wear model is applied to reproduce the stone chip behavior of two standard tests,i.e.,DIN 55996-1 and SAE-J400-2002 tests.Numerical results are found to be in good agreement with experimental data,which demonstrates the capacity of our developed method in stone chip resistance evaluation.Finally,parametric studies are conducted to numerically investigate the influences of initial velocity and test panel orientation on impact damage of automotive coatings.

Dynamic Weapon Target Assignment Based on Intuitionistic Fuzzy Entropy of Discrete Particle Swarm

Aiming at the problems of convergence-slow and convergence-free of Discrete Particle Swarm Optimization Algorithm(DPSO) in solving large scale or complicated discrete problem, this article proposes Intuitionistic Fuzzy Entropy of Discrete Particle Swarm Optimization(IFDPSO) and makes it applied to Dynamic Weapon Target Assignment(WTA). First, the strategy of choosing intuitionistic fuzzy parameters of particle swarm is defined, making intuitionistic fuzzy entropy as a basic parameter for measure and velocity mutation. Second, through analyzing the defects of DPSO, an adjusting parameter for balancing two cognition, velocity mutation mechanism and position mutation strategy are designed, and then two sets of improved and derivative algorithms for IFDPSO are put forward, which ensures the IFDPSO possibly search as much as possible sub-optimal positions and its neighborhood and the algorithm ability of searching global optimal value in solving large scale 0-1 knapsack problem is intensified. Third, focusing on the problem of WTA, some parameters including dynamic parameter for shifting firepower and constraints are designed to solve the problems of weapon target assignment. In addition, WTA Optimization Model with time and resource constraints is finally set up, which also intensifies the algorithm ability of searching global and local best value in the solution of WTA problem. Finally, the superiority of IFDPSO is proved by several simulation experiments. Particularly, IFDPSO, IFDPSO1~IFDPSO3 are respectively effective in solving large scale, medium scale or strict constraint problems such as 0-1 knapsack problem and WTA problem.

Novel Discrete Particle Swarm Optimization Based on Huge Value Penalty for Solving Engineering Problem

For the purpose of solving the engineering constrained discrete optimization problem, a novel discrete particle swarm optimization（DPSO） is proposed. The proposed novel DPSO is based on the idea of normal particle swarm optimization（PSO）, but deals with the variables as discrete type, the discrete optimum solution is found through updating the location of discrete variable. To avoid long calculation time and improve the efficiency of algorithm, scheme of constraint level and huge value penalty are proposed to deal with the constraints, the stratagem of reproducing the new particles and best keeping model of particle are employed to increase the diversity of particles. The validity of the proposed DPSO is examined by benchmark numerical examples, the results show that the novel DPSO has great advantages over current algorithm. The optimum designs of the 100-1 500 mm bellows under 0.25 MPa are fulfilled by DPSO. Comparing the optimization results with the bellows in-service, optimization results by discrete penalty particle swarm optimization（DPPSO） and theory solution, the comparison result shows that the global discrete optima of bellows are obtained by proposed DPSO, and confirms that the proposed novel DPSO and schemes can be used to solve the engineering constrained discrete problem successfully.

Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem

Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid ap- proximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimiza- tion (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.

Numerical Simulation of Gas Holdup Distribution in a Standard Rushton Stirred Tank Using Discrete Particle Method

The discrete particle method was used to simulate the distribution of gas holdup in a gas-liquid standard Rushton stirred tank. The gas phase was treated as a large number of bubbles and their trajectories were tracked with the results of motion equations. The two-way approach was performed to couple the interphase momentum exchange. The turbulent dispersion of bubbles with a size distribution was modeled using a stochastic tracking model, and the added mass force was involved to account for the effect of bubble acceleration on the surrounding fluid. The predicted gas holdup distribution showed that this method could give reasonable prediction comparable to the reported experimental data when the effect of turbulence was took into account in modification for drag coefficient.

Tidal Turbine Array Optimization Based on the Discrete Particle Swarm Algorithm

In consideration of the resource wasted by unreasonable layout scheme of tidal current turbines, which would influence the ratio of cost and power output, particle swarm optimization algorithm is introduced and improved in the paper. In order to solve the problem of optimal array of tidal turbines, the discrete particle swarm optimization(DPSO) algorithm has been performed by re-defining the updating strategies of particles’ velocity and position. This paper analyzes the optimization problem of micrositing of tidal current turbines by adjusting each turbine’s position,where the maximum value of total electric power is obtained at the maximum speed in the flood tide and ebb tide.Firstly, the best installed turbine number is generated by maximizing the output energy in the given tidal farm by the Farm/Flux and empirical method. Secondly, considering the wake effect, the reasonable distance between turbines,and the tidal velocities influencing factors in the tidal farm, Jensen wake model and elliptic distribution model are selected for the turbines’ total generating capacity calculation at the maximum speed in the flood tide and ebb tide.Finally, the total generating capacity, regarded as objective function, is calculated in the final simulation, thus the DPSO could guide the individuals to the feasible area and optimal position. The results have been concluded that the optimization algorithm, which increased 6.19% more recourse output than experience method, can be thought as a good tool for engineering design of tidal energy demonstration.

Study on the particle breakage of ballast based on a GPU accelerated discrete element method

Breakage of particles will have greatly influence on mechanical behavior of granular material(GM)under external loads,such as ballast,rockfill and sand.The discrete element method(DEM)is one of the most popular methods for simulating GM as each particle is represented on its own.To study breakage mechanism of particle breakage,a cohesive contact mode is developed based on the GPU accelerated DEM code-Blaze-DEM.A database of the 3D geometry model of rock blocks is established based on the 3D scanning method.And an agglomerate describing the rock block with a series of non-overlapping spherical particles is used to build the DEM numerical model of a railway ballast sample,which is used to the DEM oedometric test to study the particles’breakage characteristics of the sample under external load.Furthermore,to obtain the meso-mechanical parameters used in DEM,a black-analysis method is used based on the laboratory tests of the rock sample.Based on the DEM numerical tests,the particle breakage process and mechanisms of the railway ballast are studied.All results show that the developed code can better used for large scale simulation of the particle breakage analysis of granular material.

Performance characteristics of the airlift pump under vertical solid-water-gas flow conditions for conveying centimetric-sized coal particles

In this study,the installation of an airlift pump with inner diameter of 102 mm and length of 5.64 m was utilized to consider the conveying process of non-spherical coal particles with density of 1340 kg/m3 and graining 25-44.5 mm.The test results revealed that the magnitude of increase in the solid transport rate due to the changes in the three tested parameters between compressed air velocity,submergence ratio,and feeding coal possibility was not the same,which are stand in range of 20%,75%,and 40%,respectively.Hence,creating the optimal airlift pump performance is highly dependent on submergence ratio.More importantly,we measured the solid volume fraction using the method of one-way valves in order to minimize the disadvantages of conventional devices,such as fast speed camera and conductivity ring sensor.The results confirmed that the volume fraction of the solid phase in the transfer process was always less than 12%.To validate present experimental data,the existing empirical correlations together with the theoretical equations related to the multiphase flow was used.The overall agreement between the theory and experimental solid delivery results was particularly good instead of the first stage of conveying process.This drawback can be corrected by omitting the role of friction and shear stress at low air income velocity.It was also found that the model developed by Kalenik failed to predict the performance of our airlift operation in terms of the mass flow rate of the coal particles.

Time effect and prediction of broken rock bulking coefficient on the base of particle discrete element method

Bulking characteristics of gangue are of great significance for the stability of goafs in mining overburden in the caving zones.In this paper,a particle discrete element method with clusters to represent gangue was adopted to explore the bulking coefficient time effect of the broken rock in the caving zone under three-dimensional triaxial compression condition.The phenomena of stress corrosion,deformation,and failure of rock blocks were simulated in the numerical model.Meanwhile,a new criterion of rock fragments damage was put forward.It was found that the broken rock has obvious viscoelastic properties.A new equation based on the Burgers creep model was proposed to predict the bulking coefficient of broken rock.A deformation characteristic parameter of the prediction equation was analyzed,which can be set as a fixed value in the mid-and long-term prediction of the bulking coefficient.There are quadratic function relationships between the deformation characteristic parameter value and Talbot gradation index,axial pressure and confining pressure.

A New Clustering Algorithm Using Adaptive Discrete Particle Swarm Optimization in Wireless Sensor Network

Wireless sensor networks (WSNs) are mainly characterized by their limited and non-replenishable energy supply. Hence, the energy efficiency of the infrastructure greatly affects the network lifetime. Clustering is one of the methods that can expand the lifespan of the whole network by grouping the sensor nodes according to some criteria and choosing the appropriate cluster heads(CHs). The balanced load of the CHs has an important effect on the energy consumption balancing and lifespan of the whole network. Therefore, a new CHs election method is proposed using an adaptive discrete particle swarm optimization (ADPSO) algorithm with a fitness value function considering the load balancing and energy consumption. Simulation results not only demonstrate that the proposed algorithm can have better performance in load balancing than low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), and dynamic clustering algorithm with balanced load (DCBL), but also imply that the proposed algorithm can extend the network lifetime more.

NUMERICAL STUDY OF PARTICLE DISTRIBUTION IN WAKE OF LIQUID-PARTICLE FLOWS PAST A CIRCULAR CYLINDER USING DISCRETE VORTEX METHOD

Particle-laden water flows past a circular cylinder were numerically investigated. The discrete vortex method （DVM） was employed to evaluate the unsteady water flow fields and a Lagrangian approach was applied for tracking individual solid particles. A dispersion function was defined to represent the dispersion scale of the particle. The wake vortex patterns, the distributions and the time series of dispersion functions of particles with different Stokes numbers were obtained. Numerical results show that the particle distribution in the wake of the circular cylinder is closely related to the particle＇s Stokes number and the structure of wake vortices： （1） the intermediate sized particles with Stokes numbers, St, of 0.25, 1.0 and 4.0 can not enter the vortex cores and concen- trate near the peripheries of the vortex structures, （2） in the circular cylinder wake, the dispersion intensity of particles decreases as St is increased from 0.25 to 4.0.