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.

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.

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.

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.

STUDY OF THE RELATIONSHIP BETWEEN IWC AND Z FOR NONSPHERICAL ICE PARTICLES AT MILLIMETER WAVELENGTH

Ice water content(IWC) plays important roles in weather and climate change.Determining the IWCs of cirrus clouds with millimeter-wavelength radar can be problematic due to influences of ice particle rotation on their backscattering cross sections.We here introduce models to describe the radiation patterns of six nonspherical particles of specific sizes.Simulations using HFSS software were applied to describe the differences resulting from different orientations and equivalent spheres.A double exponential function was used for fitting to describe the relationship between the particles' maximum sizes and backscattering cross sections.The backscattering cross sections of nonspherical ice particles were computed by the method of moment,and those of the equivalent spherical particles were computed by Lorenz-Mie theory for three different orientations:fixed,horizontal,and random.Assuming that a mixture of nonspherical ice particles follows the B-H mixing model,the size distribution of cirrus particles obeys the exponential distribution measured by NASA in 2007.By computing the IWCs of cirrus clouds,which follows the above mentioned B-H model and exponential distribution,the radar reflectivity factors of nonspherical ice particles and equivalent spheres at three different orientations can be computed.Subsequently,the IWC results can be acquired by inputting the radar reflectivity variables into the well-known IWC-Z formula.The analysis described here demonstrates that when using the radar reflectivity Z,the orientation must be considered in order to determine the IWC.Using equivalent sphere theory,the derived IWCs underestimate the actual IWCs.These results are important for accurately retrieving the microphysical parameters of cirrus clouds.

Discrepancy between Ice Particles and Ice Nuclei in Mixed Clouds: Critical Aspects

Measurements of ice crystal concentrations in mixed clouds tend to exceed ice nucleus concentrations measured in nearby clear air. This discrepancy is a source of uncertainty in climate change projections as the radiative properties of mixed phase clouds are largely determined by their liquid and ice water content. The ice enhancement process can sometimes depend on secondary ice production, which can occur through ice crystal fracture during sublimation, cloud drop shattering during freezing or following collision with ice particles. However, the discrepancy is observed even in mixed clouds where only primary ice nucleation processes occur. Several hypotheses have been suggested for the observed discrepancies. One factor could be the existence in clouds of pockets of high vapor supersaturation formed by droplet freezing or removal of small droplets by collision with larger droplets, associated with the fact that ice crystal concentration increases with water supersaturation. However, ice crystal concentrations are usually measured at near water saturation. Additional factors could be drop freezing during evaporation and activation of droplet evaporation residues. Here we suggest that a major factor could be underestimation of the contact freezing mode as it is not measured in experimental campaigns and seldom considered in nucleation models. Laboratory experiments give only incomplete answers to the important questions concerning the contact freezing mode, e.g. what fraction of the aerosol particles that come into contact with the droplet surface results in a freezing event and what is the influence of particle type and size, air temperature and relative humidity. As supercooled droplets grow or evaporate in mixed clouds, phoretic forces should play an important role in the collision efficiency between aerosol and droplets, and consequently in contact freezing. A further question is the possibility that aerosol, usually not active in deposition or condensation/immersion freezing, can trigger ice nucleation by colliding with supercooled droplets.

Simulation on hydrodynamics of non-spherical particulate system using a drag coefficient correlation based on artificial neural network

Fluidization of non-spherical particles is very common in petroleum engineering.Understanding the complex phenomenon of non-spherical particle flow is of great significance.In this paper,coupled with two-fluid model,the drag coefficient correlation based on artificial neural network was applied in the simulations of a bubbling fluidized bed filled with non-spherical particles.The simulation results were compared with the experimental data from the literature.Good agreement between the experimental data and the simulation results reveals that the modified drag model can accurately capture the interaction between the gas phase and solid phase.Then,several cases of different particles,including tetrahedron,cube,and sphere,together with the nylon beads used in the model validation,were employed in the simulations to study the effect of particle shape on the flow behaviors in the bubbling fluidized bed.Particle shape affects the hydrodynamics of non-spherical particles mainly on microscale.This work can be a basis and reference for the utilization of artificial neural network in the investigation of drag coefficient correlation in the dense gas-solid two-phase flow.Moreover,the proposed drag coefficient correlation provides one more option when investigating the hydrodynamics of non-spherical particles in the gas-solid fluidized bed.

Distribution of transparent exopolymer particles and their response to phytoplankton community structure changes in the Amundsen Sea,Antarctica

To understand the response of transparent exopolymer particles(TEP)to the changes in phytoplankton communities caused by melting sea ice,we collected samples from the polynya and open ocean affected by the Antarctic circumpolar current in the Amundsen Sea.TEP,pigments,and other environmental factors were analyzed.The results showed that high TEP content was mainly found in the polynya,and was higher in the surface layer than in the deep layer.The main factor that affected TEP distribution was the phytoplankton community.In the polynya area,the phytoplankton were dominated by low-iron Haptophyta.In the Antarctic circumpolar current region affected by ice-melting water,the dominant species was diatom type II.Our results revealed that low-iron Haptophyta may be the main contributors to TEP content.

Multi-level DEM study on silo discharge behaviors of non-spherical particles

The silo discharge of non-spherical particles has been widely practiced in engineering processes, yet the understanding of multi-level mechanisms during solid transportation is still lacking. In this study, a high-fidelity super-ellipsoid Discrete Element Method (DEM) model is established to investigate the discharge behaviors of non-spherical particles with different size distributions. After the comprehensive model validations, we investigated the effects of particle shape (aspect ratio and particle sharpness) on the particle level discharge behaviors. The discharge rates of the ellipsoid particles used in the current work are larger than the spherical particles due to the larger solid fraction. The discharge rates of the cuboid-like particles are determined by the combined effect of the solid fraction and the contact force. Parcel level data show that the translational movements of the ellipsoid particles are more ordered, which is supported by the global level data. Strong correlations exist between the particle level and parcel level data, especially the ellipsoid particles and the large particles in the polydispersed cases.

NUMERICAL SIMULATIONS OF POLARIZED SCATTERING FROM RANDOM CLUSTERS OF SPATIALLY-ORENTED, NON-SPHERICAL SCATTERS

Employing multiple scattering formulation of T-matrix method, numerical simulations are developed and applied to polarized scattering from random clusters of spatially-oriented, non-spherical particles. Polarized scattering is numerically presented for the functional dependence on particle shape, size, spatial distribution and orientation, and other physical parameters. Numerical calculations of backscattering from randomly clustered particles are well compared with that from independent particles and clusters. It can be seen that spatial distribution and orientation of non-spherical particles can have significant effect on scattering.

Elementary Particles Result from Space-Time Quantization

We justify and extend the standard model of elementary particle physics by generalizing the theory of relativity and quantum mechanics. The usual assumption that space and time are continuous implies, indeed, that it should be possible to measure arbitrarily small intervals of space and time, but we ignore if that is true or not. It is thus more realistic to consider an extremely small “quantum of length” of yet unknown value a. It is only required to be a universal constant for all inertial frames, like c and h. This yields a logically consistent theory and accounts for elementary particles by means of four new quantum numbers. They define “particle states” in terms of modulations of wave functions at the smallest possible scale in space-time. The resulting classification of elementary particles accounts also for dark matter. Antiparticles are redefined, without needing negative energy states and recently observed “anomalies” can be explained.

Study on Ice Regime Forecast Based on SVR Optimized by Particle Swarm Optimization Algorithm

[Objective] The research aimed to study forecast models for frozen and melted dates of the river water in Ningxia-Inner Mongolia section of the Yellow River based on SVR optimized by particle swarm optimization algorithm. [Method] Correlation analysis and cause analysis were used to select suitable forecast factor combination of the ice regime. Particle swarm optimization algorithm was used to determine the optimal parameter to construct forecast model. The model was used to forecast frozen and melted dates of the river water in Ningxia-Inner Mongolia section of the Yellow River. [Result] The model had high prediction accuracy and short running time. Average forecast error was 3.51 d, and average running time was 10.464 s. Its forecast effect was better than that of the support vector regression optimized by genetic algorithm (GA) and back propagation type neural network (BPNN). It could accurately forecast frozen and melted dates of the river water. [Conclusion] SVR based on particle swarm optimization algorithm could be used for ice regime forecast.

A Review of Thermo- and Diffusio-Phoresis in the Atmospheric Aerosol Scavenging Process. Part 2: Ice Crystal and Snow Scavenging

The role of phoretic forces in the identification of particles acting as ice nuclei in mixed phase cloud is discussed. A method used to identify the effective ice nucleating particles is to sample ice crystals, which are afterwards sublimated, and to examine the particles remaining after evaporation. The procedure takes into account only crystal with a maximum diameter of 20 μm, by assuming that small crystals do not scavenge aerosol during growth, and therefore that crystals contain only the effective nucleating particles. This assumption is questionable, however, as experiments have shown that even small ice crystals can scavenge aerosol. Another approach has been to compare the number and elemental composition of residual particles in small ice crystals and of aerosol near the cloud. By considering as example soot and black carbon aerosol, contradictory conclusions on their importance in the processes of ice nucleation have been reported in the literature. We suggest that, in addition to physico-chemical properties of soot/carbon aerosol particles, even the microphysical and environmental parameters involved in the transition of aerosol from gas phase to ice crystals in cloud should be considered. The contribution of phoretic forces should also be considered. After initial growth ice crystals can continue to grow by water vapour diffusion. Laboratory experiments confirm the contribution of diffusiophoresis with Stefan flow in the scavenging by snow crystals up to 3 mm in diameter. The particle scavenging efficiency of snow crystals is related to crystalline shape and depends on air relative humidity and temperature.

Axial segregation characteristics and size-induced flow behavior of particles in a novel rotary drum with curved sidewalls

Particle mixing and segregation are common phenomena in rotary drums,which are challenging to be controlled and driven artificially in powder technology.In this work,the discrete element method(DEM)was applied to construct the novel rotary drum composed of different shaped curved sidewalls.By varying the operation parameters of particle and sidewall shapes as well as the length-to-diameter(L/D)ratio of drums,the axial mixing and segregation processes of binary size-induced particles were investigated.The results show that the axial flow velocity of the particle mixtures is noticeably weakened once the particle angularity increases,making the non-spherical particles to mix better in rotary drums compared to the spherical particles.Besides,in the short drums with size-induced spherical particles,the axial segregation characteristics are significantly enhanced by the convex sidewalls while suppressed by the concave sidewalls.However,for size-induced non-spherical particles,the axial segregation structure can be present in rotary drums with plane and concave sidewalls while not in drums with convex sidewalls.Moreover,the axial segregation band structure of spherical particles eventually increases proportionally with the increased drum L/D ratios.In contrast,the non-spherical particles cannot form obvious multi-proportional segregation bands.

Study on a semi-resolved CFD-DEM method for rod-like particles in a gas-solid fluidized bed

Based on a semi-resolved CFD-DEM coupling method,this study proposed a method that uses the minimum distance between the fluid grid and the particle boundary as a reference value to determine the degree of influence of the target fluid grid on the particle's drag force.A fluidized bed of rod-like particles was chosen as a typical case to investigate the effect of different fluid grid scales on various fluidized bed characteristic parameters.The calculation performance of the semi-resolved and unre-solved CFD-DEM coupling algorithm on key fluidized bed characteristic parameters such as average pressure drop,particle frequency distribution with bed height,and particle orientation distribution were compared.It was found that the semi-resolved CFD-DEM coupling algorithm gradually obtained results with higher consistency with decreasing fluid grid scale for key parameters such as particle frequency distribution with bed height,particle orientation distribution,and time-history mixing index,exhibiting a phenomenon similar to grid independence in fluid simulation.By comparing with experimental results,it was verified that the semi-resolved CFD-DEM coupling algorithm can be applied to simulate multi-granular gas-solid systems with fluid grid scales equivalent to particle scales.This algorithm solves the limitation of fluid grid scale in the unresolved CFD-DEM coupling framework and improves the grid adaptability of the CFD-DEM coupling simulation algorithm.

Analysis of extinction characteristics of non-spherical biological particle aggregates [Invited]

In this study,a method was presented to accurately obtain the extinction characteristics of the non-spherical biological particle aggregates.Based on the multi-sphere particle model of non-spherical particles,a randomly oriented aggregation model was firstly built to construct the aggregates.The discrete-dipole approximation method was used to calculate the extinction characteristics of aggregates in the 3–14 μm waveband.The average mass extinction coefficients of three materials are 0.802 m~2/g,0.907 m~2/g,and 0.866 m~2/g in the 3–5 μm waveband and 0.590 m~2/g,0.402 m~2/g,and 0.523 m~2/g in the8–14 μm band,respectively.Smoke chamber experimental results are in good agreement with theoretical analyses.

Numerical investigation of non-spherical particle deposition characteristics on filter media

In the building environment,PM2.5 seriously affects people’s health and quality of life,so it is necessary to study the particle deposition characteristics.In addition,it is essential for a thorough investigation of the dust removal mechanism to understand the non-spherical particles deposition characteristics.The stacking angle experiment was used to calibrate the discrete element simulation parameters.And four simulation methods(CFD-DPM,CFD-DEM,API interface loading drag model based on EDEM software and EDEM simulation)were used to numerically simulate the non-spherical particles deposition characteristics.The optimal simulation method EDEM was applied to study the non-spherical particles deposition characteristics in filter media,which saves the calculation time obviously.On this basis,the particle parameters on the particle deposition characteristics of filter media were investigated.The results show that the deposition rate of non-spherical(special shape)particles with the same volume is basically consistent on the filter media,hence it is more realistic that the dust actual shape is simplified into the triangular-shaped particles.As the particle size increases,the number of deposited particles on the filter media decreases.And the larger the particle size,the more dispersed the distribution.It has a significant impact on the number of particles deposited on the filter media when the particle velocity is 0.1 m/s.The particle deposits to the lower part of the filter media in the form of a parabola and deviates from the outlet seriously at 0.1 m/s.Moreover,it has little effect on the number of particle deposition at the other velocities,and most particles are deposited on the upper part of the filter media with the increase of particle velocity.

Fluidization of non-spherical particles:Sphericity,Zingg factor and other fluidization parameters

A comparison of sphericity and Zingg factor for particle morphology and description of fluidized-bed dynamics are presented. It is found that Zingg factor Fz = LH/B2 （where L, H and B are, respectively, the length, breadth and height of a particle） well describes the effect of particle morphology. Experimental results show that non-spherical particles give poor fluidizing quality as compared to spherical particles in terms of pressure drop, Umf, etc. With the same volume-equivalent diameter, non-spherical particles have lower Umf and fluidizing coefficient 8. Some smooth curves have been obtained between the parameters 8, Umf and Fz. The quality of fluidization could be evaluated by fluidizing coefficient, which has been correlated to the Zingg factor and minimum fluidizing velocity in this paper.

Settling behavior of non-spherical particles in power-law fluids:Experimental study and model development

Solid-particle settling occurs in many natural and industrial processes, such as in the transportation of drilling cuttings and fracturing proppant. Knowledge of the drag coefficient and settling velocity of cuttings and proppant is of significance to hydraulics design, wellbore cleanout, and fracture optimization. We conducted 553 tests to investigate the settling characteristics of spherical and non-spherical particles in power-law fluids. Three major particle shapes (spherical, cubic, and cylindrical) and eight different particle sphericities were used to simulate cuttings and proppant, and power-law fluids were applied to simulate drilling and fracturing fluids. Based on the data analysis, a new drag coefficient-particle Reynolds number correlation was developed to determine the drag coefficient in a power-law fluid for spherical and non-spherical particles. The drag coefficient increases as the sphericity decreases for the same particle Reynolds number. For a specific particle shape, the drag coefficient decreases as the particle Reynolds number increases, but the decreasing trend is reduced at high particle Reynolds number conditions. An explicit settling-velocity equation was proposed to calculate the settling velocity of spherical and non-spherical particles in power-law fluids by considering the effect of sphericity. A suitable range for the proposed model is 0.0001 < Re <200, 0.471 <φ< 1, and 0.505 < n < 1. An illustrative example is presented to show how to calculate the drag coefficient and settling velocity in power-law fluids with given particle and fluid properties.