Ultrasonic cavitation involves dynamic oscillation processes induced by small bubbles in a liquid under the influence of ultrasonic waves. This study focuses on the investigation of shape and diffusion instabilities o...Ultrasonic cavitation involves dynamic oscillation processes induced by small bubbles in a liquid under the influence of ultrasonic waves. This study focuses on the investigation of shape and diffusion instabilities of two bubbles formed during cavitation. The derived equations for two non-spherical gas bubbles, based on perturbation theory and the Bernoulli equation, enable the analysis of their shape instability. Numerical simulations, utilizing the modified Keller–Miksis equation,are performed to examine the shape and diffusion instabilities. Three types of shape instabilities, namely, Rayleigh–Taylor,Rebound, and parametric instabilities, are observed. The results highlight the influence of initial radius, distance, and perturbation parameter on the shape and diffusion instabilities, as evidenced by the R_0–P_a phase diagram and the variation pattern of the equilibrium curve. This research contributes to the understanding of multiple bubble instability characteristics, which has important theoretical implications for future research in the field. Specifically, it underscores the significance of initial bubble parameters, driving pressure, and relative gas concentration in determining the shape and diffusive equilibrium instabilities of non-spherical bubbles.展开更多
Flow behaviors of four kinds of granular particles(i.e. sphere,ellipsoid,hexahedron and binary mixture of sphere and hexahedron) in rectangular hoppers were experimentally studied. The effects of granular shape and ho...Flow behaviors of four kinds of granular particles(i.e. sphere,ellipsoid,hexahedron and binary mixture of sphere and hexahedron) in rectangular hoppers were experimentally studied. The effects of granular shape and hopper structure on flow pattern,discharge fraction,mean particle residence time and tracer concentration distribu-tion were tested based on the visual observation and particle tracer technique. The results show that particle shape affects significantly the flow pattern. The flow patterns of sphere,ellipsoid and binary mixture are all parabolic shape,and the flow pattern shows no significant difference with the change of wedge angle. The flowing zone be-comes more sharp-angled with the increasing outlet size. The flow pattern of hexahedron is featured with straight lines. The discharge rates are in increasing order from hexahedron,sphere,binary mixture to ellipsoid. The dis-charge rate also increases with the wedge angle and outlet size. The mean particle residence time becomes shorter when the outlet size increases. The difference of mean particle residence time between the maximum and minimum values decreases as the wedge angle increases. The residence time of hexahedron is the shortest. The tracer concen-tration distribution of hexahedron at any height is more uniform than that of binary mixture. The tracer concentra-tion of sphere in the middle is lower than that near the wall,and the contrary tendency is found for ellipsoid particles.展开更多
Non-spherical colloidal silica nanoparticle was prepared by a simple new method, and its particle size distribution and shape morphology were characterized by dynamic light scattering(DLS) and the Focus Ion Beam(FIB) ...Non-spherical colloidal silica nanoparticle was prepared by a simple new method, and its particle size distribution and shape morphology were characterized by dynamic light scattering(DLS) and the Focus Ion Beam(FIB) system. This kind of novel colloidal silica particles can be well used in chemical mechanical polishing(CMP) of sapphire wafer surface. And the polishing test proves that non-spherical colloidal silica slurry shows much higher material removal rate(MRR) with higher coefficient of friction(COF) when compared to traditional large spherical colloidal silica slurry with particle size 80 nm by DLS. Besides, sapphire wafer polished by non-spherical abrasive also has a good surface roughness of 0.460 6 nm. Therefore, non-spherical colloidal silica has shown great potential in the CMP field because of its higher MRR and better surface roughness.展开更多
Gas atomization was usually regarded as a good method for producing the spherical or approximate spherical powders. We found a lot of non-spherical powders in production processes, especially in larger particle size d...Gas atomization was usually regarded as a good method for producing the spherical or approximate spherical powders. We found a lot of non-spherical powders in production processes, especially in larger particle size distribution area. The causes of producing non-spherical powders are explained and some analyses are done in order to find a better condition of producing spherical powders in this paper. The following morphologies were obtained by atomized Fe50 Co50 and pure iron and investigated by scanning electron microscopy （SEM）.展开更多
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,t...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.展开更多
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 ...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.展开更多
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 equat...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).展开更多
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 resi...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.展开更多
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 ...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.展开更多
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 scat...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.展开更多
Non-spherical particles are extensively encountered in the process industry such as feedstock or catalysts e.g.,energy,food,pharmaceuticals,and chemicals.The design of equipment used to process these particles is high...Non-spherical particles are extensively encountered in the process industry such as feedstock or catalysts e.g.,energy,food,pharmaceuticals,and chemicals.The design of equipment used to process these particles is highly dependent upon the accurate and reliable modeling of hydrodynamics of particulate media involved.Drag coefficient of these particles is the most significant of all parameters.A universal model to predict the drag coefficient of such particles has not yet been developed due to the diversity and complexity of particle shapes and sizes.Taking this into consideration,we propose a unique approach to model the drag coefficient of non-spherical particles using machine learning(ML)to move towards generalization.A comprehensive database of approximately five thousand data points from reliable experiments and high-resolution simulations was compiled,covering a wide range of conditions.The drag coefficient was modeled as a function of Reynolds number,sphericity,Corey Shape Factor,aspect ratio,volume fraction,and angle of incidence.Three ML techniques—Artificial Neural Networks,Random Forest,and AdaBoost—were used to train the models.All models demonstrated strong generalization when tested on unseen data.However,AdaBoost outperformed the others with the lowest MAPE(20.1%)and MRD(0.069).Additional analysis on excluded data confirmed the robust predictive abilities and generalization of the proposed model.The models were also evaluated across three flow regimes—Stokes,transitional,and turbulent—to further assess their generalization.A comparative analysis with well-known empirical correlations,such as Haider and Levenspiel and Chien,showed that all ML models outperformed traditional approaches,with AdaBoost achieving the best results.The current work demonstrates that new generated ML techniques can be reliably used to predict drag coefficient of non-spherical particles paving way towards generalization of ML approach.展开更多
Biomass energy is considered a promising renewable energy resource to cope with global carbon neutrality goals and the ongoing energy crisis. However, the irregular shapes and varying sizes of milled biomass particles...Biomass energy is considered a promising renewable energy resource to cope with global carbon neutrality goals and the ongoing energy crisis. However, the irregular shapes and varying sizes of milled biomass particles hinder their effective usage in biomass reactors for energy generation. Previous research on non-spherical particles has mainly focused on single-particle systems, with limited studies on binary mixtures. This study employs CFD-DEM method with superquadric shape representation to investigate the mixing behavior of spherical and cylindrical particles in a spouted fluidized bed. The results show that increasing the aspect ratio of cylindrical particles increases accumulation in dead zones. A higher proportion of cylindrical particles significantly reduces spouting height and makes the V-shaped dead zone more evidence. During spouting from a static state, cylindrical particles exhibit notable changes in pitch angle, transitioning from horizontal to vertical orientations, with these trends becoming more pronounced at higher aspect ratios. These findings provide insight into the mixing behavior of binary particle system of spherical and non-spherical particles, and offer a guidance for the reactor operation with these particle types.展开更多
This paper introduces a resolved coupling method based on the LBM(Lattice Boltzmann Method) and DEM(Discrete Element Method)for simulating fluid-particle interactions involving non-spherical particles.The super-ellips...This paper introduces a resolved coupling method based on the LBM(Lattice Boltzmann Method) and DEM(Discrete Element Method)for simulating fluid-particle interactions involving non-spherical particles.The super-ellipsoid model is applied so that a wide range of particle shapes can be represented with high accuracy and efficiency,enabling a detailed investigation of shape effects on flow behavior.The proposed method is validated by comparing simulation results with experimental data on the sedimentation of both spherical and non-spherical particles.Then a fluidized bed system containing different kinds of non-spherical particles is studied and the influence of particle shape on the flow field is investigated.The result further confirms the accuracy and robustness of this method in complex multiphase flow systems.Compared to existing LBM-DEM coupling approaches,this study is more accurate and efficient for simulating flow fields involving particles with smooth surfaces,offering a powerful tool for the study of multiphase systems with regular non-spherical particles.展开更多
Gas pulsation is an efficient enhancing way for fluidized bed drying process.In this work,the influence of gas pulsation on mass and heat transfer performance in a fluidized bed with non-spherical wet particles is num...Gas pulsation is an efficient enhancing way for fluidized bed drying process.In this work,the influence of gas pulsation on mass and heat transfer performance in a fluidized bed with non-spherical wet particles is numerically investigated via the computational fluid dynamics−discrete element method(CFD-DEM)approach,where the liquid transfer between particles and the heat transfer by liquid bridge are considered.The aspect ratio effect of non-spherical particle on drying process is revealed.It is found that the increase of aspect ratio can weaken the overall drying quality.The influence of gas pulsation on the drying of non-spherical particle is analyzed.The results reveal that adjusting a suitable gas pulsation mode can efficiently regulate the drying process of non-spherical wet particles with greater aspect ratios.展开更多
Packed bed reactors of non-spherical particles are widely used in chemical industry with the aim to obtain a high active surface area and achieve a homogeneous flow.Despite this,little is known about the arrangement o...Packed bed reactors of non-spherical particles are widely used in chemical industry with the aim to obtain a high active surface area and achieve a homogeneous flow.Despite this,little is known about the arrangement of particles within the bed and the influence of this arrangement on the fluid flow distribution.Magnetic Resonance Imaging (MRI) is a non-invasive tomographic imaging technique that allows 3D visualisation of the packing and flow structure.However,the individual particle information is not obtained using MRI.In this work we investigate different particle detection methods to retrieve the particle position and orientation from MRI images.Results show the successful reconstruction of random packing structures of various non-spherical particle shapes: ellipsoid,spherocylinder,cylinder and cube.The applicability of each method in relation to the particle shape,as well as strengths and drawbacks of each particle detection method are discussed.This paper shows the ability to reconstruct real packed beds of non-spherical particle shapes from MRI images,which opens several research opportunities in the field of chemical engineering.展开更多
Background:Sudden sensorineural hearing loss(SSNHL),often associated with tinnitus,significantly impacts individuals'quality of life.Current treatments,such as free drugs via intravenous or intratympanic(IT)admini...Background:Sudden sensorineural hearing loss(SSNHL),often associated with tinnitus,significantly impacts individuals'quality of life.Current treatments,such as free drugs via intravenous or intratympanic(IT)administration of dexamethasone(DEX)and lidocaine,face limitations like low bioavailability and rapid drug clearance.To address these challenges,we developed a local co-delivery system combining DEX microcrystals(DEX MCs)and lidocaine-loaded poly(lactic-co-glycolic acid)(PLGA)non-spherical microparticles(LPNMs)for sustained drug release in the inner ear.Methods:DEX MCs and LPNMs were prepared using the traditional precipitation technique and double emulsion-solvent evaporation,respectively.After characterizing physicochemical properties and drug release kinetics,they were dispersed in sodium hyaluronate solution for IT injection,then in vivo pharmacokinetics and biocompatibility in guinea pigs were studied.Results:DEX MCs exhibited stable dissolution,while LPNMs provided sustained lidocaine release,reducing potential side effects.In vivo studies in guinea pigs demonstrated prolonged drug retention in the perilymph and improved pharmacokinetics.Histological evaluation confirmed the good biocompatibility of this combined delivery system,with no significant inner ear damage observed.Conclusion:This co-delivery system can be used as a depot for delivering both DEX and lidocaine to the inner ear and offers a promising approach for the synergistic treatment of SSNHL associated with tinnitus.展开更多
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, b...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.展开更多
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 ...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.展开更多
Screw conveyors are extensively used in modern industry such as metallurgy,architecture and pharmaceutical due to their high-efficiency in the transportation of granular materials.And substantial efforts have been dev...Screw conveyors are extensively used in modern industry such as metallurgy,architecture and pharmaceutical due to their high-efficiency in the transportation of granular materials.And substantial efforts have been devoted to the study of the screw conveyors.Numerical method is an effective way to study screw conveyor.However,previous studies have mainly focused in the regime of spherical particles while the in-depth investigations for non-spherical particles that should be the most encountered in practical applications are still limited.In view of the above situations,discrete element method(DEM),which has been widely accepted in simulating the discrete systems,is utilized to investigate the conveying process of non-spherical particles in a horizontal screw conveyor,with particles being modeled by super-ellipsoids.In addition,a wear model called SIEM(Shear Impact Energy Model)is incorporated into DEM to predict the wear of screw conveyor.The DEM simulation results demonstrate that the particle shape is influential for the flow behaviors of particles and the wear of conveyor.The conveying performance evaluated quantitatively of both mass flow rate and power consumption is subsequently obtained to investigate the effect of sphericity of particle with different operation parameters.Moreover,particle collision frequency and collision energy consumption are acquired to investigate the possible particle breakage between particles and screw blade.The comparisons between particle-particle collision and particle-wall collision reveal that particles with large shape index have more possibility to be damaged in particle-wall impingement.展开更多
We investigated the deposition pattern of microparticles with different particle diameters, shape factors, and initial flow conditions in a realistic human upper respiratory tract model. We identified a close relation...We investigated the deposition pattern of microparticles with different particle diameters, shape factors, and initial flow conditions in a realistic human upper respiratory tract model. We identified a close relationship between the deposition fraction and the particle shape factor. The deposition fraction of the particles decreased sharply with increasing particle shape factor because of the decreasing drag force. We also found that the deposition varied at different positions in the upper respiratory tract. At low shape factors, the highest fraction of particles deposited at the mouth and pharynx. However, with increasing shape factor, the deposition fraction in the trachea and lungs increased. Moreover, for a given shape factor, larger particles deposited at the mouth and pharynx, which indicates that the deposition fraction of microparticles in the human upper respiratory tract is affected first and foremost by particle inertia as well as by the drag force.展开更多
基金Project supported by the Scientific Research Project of Higher Education in the Inner Mongolia Autonomous Region (Grant No.NJZY23100)。
文摘Ultrasonic cavitation involves dynamic oscillation processes induced by small bubbles in a liquid under the influence of ultrasonic waves. This study focuses on the investigation of shape and diffusion instabilities of two bubbles formed during cavitation. The derived equations for two non-spherical gas bubbles, based on perturbation theory and the Bernoulli equation, enable the analysis of their shape instability. Numerical simulations, utilizing the modified Keller–Miksis equation,are performed to examine the shape and diffusion instabilities. Three types of shape instabilities, namely, Rayleigh–Taylor,Rebound, and parametric instabilities, are observed. The results highlight the influence of initial radius, distance, and perturbation parameter on the shape and diffusion instabilities, as evidenced by the R_0–P_a phase diagram and the variation pattern of the equilibrium curve. This research contributes to the understanding of multiple bubble instability characteristics, which has important theoretical implications for future research in the field. Specifically, it underscores the significance of initial bubble parameters, driving pressure, and relative gas concentration in determining the shape and diffusive equilibrium instabilities of non-spherical bubbles.
基金Supported by the National Natural Science Foundation of China （50706007 50976025） the National Key Program of Basic Research in China （2010CB732206）+1 种基金 the Foundation of Excellent Young Scholar of Southeast University （4003001039） the Collaboration Project of China and British （2010DFA61960）
文摘Flow behaviors of four kinds of granular particles(i.e. sphere,ellipsoid,hexahedron and binary mixture of sphere and hexahedron) in rectangular hoppers were experimentally studied. The effects of granular shape and hopper structure on flow pattern,discharge fraction,mean particle residence time and tracer concentration distribu-tion were tested based on the visual observation and particle tracer technique. The results show that particle shape affects significantly the flow pattern. The flow patterns of sphere,ellipsoid and binary mixture are all parabolic shape,and the flow pattern shows no significant difference with the change of wedge angle. The flowing zone be-comes more sharp-angled with the increasing outlet size. The flow pattern of hexahedron is featured with straight lines. The discharge rates are in increasing order from hexahedron,sphere,binary mixture to ellipsoid. The dis-charge rate also increases with the wedge angle and outlet size. The mean particle residence time becomes shorter when the outlet size increases. The difference of mean particle residence time between the maximum and minimum values decreases as the wedge angle increases. The residence time of hexahedron is the shortest. The tracer concen-tration distribution of hexahedron at any height is more uniform than that of binary mixture. The tracer concentra-tion of sphere in the middle is lower than that near the wall,and the contrary tendency is found for ellipsoid particles.
基金Funded by the National Major Scientific and Technological Special Project during the Twelfth Five-year Plan Period(No.2009ZX02030-1)the National Natural Science Foundation of China(No.51205387)the Science and Technology Commission of Shanghai(No.11nm0500300),the Science and Technology Commission of Shanghai(No.14XD1425300)
文摘Non-spherical colloidal silica nanoparticle was prepared by a simple new method, and its particle size distribution and shape morphology were characterized by dynamic light scattering(DLS) and the Focus Ion Beam(FIB) system. This kind of novel colloidal silica particles can be well used in chemical mechanical polishing(CMP) of sapphire wafer surface. And the polishing test proves that non-spherical colloidal silica slurry shows much higher material removal rate(MRR) with higher coefficient of friction(COF) when compared to traditional large spherical colloidal silica slurry with particle size 80 nm by DLS. Besides, sapphire wafer polished by non-spherical abrasive also has a good surface roughness of 0.460 6 nm. Therefore, non-spherical colloidal silica has shown great potential in the CMP field because of its higher MRR and better surface roughness.
文摘Gas atomization was usually regarded as a good method for producing the spherical or approximate spherical powders. We found a lot of non-spherical powders in production processes, especially in larger particle size distribution area. The causes of producing non-spherical powders are explained and some analyses are done in order to find a better condition of producing spherical powders in this paper. The following morphologies were obtained by atomized Fe50 Co50 and pure iron and investigated by scanning electron microscopy （SEM）.
基金the financial support by the National Natural Science Foundation of China(Grant No.51706055).
文摘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.
基金supported by the NSFC Major Project (Grant Nos. 42090030, and 42090032)the National Natural Science Foundation of China (Grant Nos. 42022038, and 42075155)the National Key Research and Development Program (2019YFC1510400)
文摘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.
基金Project supported by the Major Program of the National Natural Science Foundation of China(No.91852102)。
文摘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).
基金supported by the National Key R&D Program of China(No.2017YFE0117300)the Science and Technology Planning Project of Guangzhou(No.201804020065)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.311021013).
文摘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.
基金financially supported by the National Natural Science Foundation of China(Grant No.51706055).
文摘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.
基金Supported by the National Natural Science Foundation of China the Shanghai Centre for Applied Physicsthe Shanghai Research and Development Foundation of Applied materials
文摘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.
文摘Non-spherical particles are extensively encountered in the process industry such as feedstock or catalysts e.g.,energy,food,pharmaceuticals,and chemicals.The design of equipment used to process these particles is highly dependent upon the accurate and reliable modeling of hydrodynamics of particulate media involved.Drag coefficient of these particles is the most significant of all parameters.A universal model to predict the drag coefficient of such particles has not yet been developed due to the diversity and complexity of particle shapes and sizes.Taking this into consideration,we propose a unique approach to model the drag coefficient of non-spherical particles using machine learning(ML)to move towards generalization.A comprehensive database of approximately five thousand data points from reliable experiments and high-resolution simulations was compiled,covering a wide range of conditions.The drag coefficient was modeled as a function of Reynolds number,sphericity,Corey Shape Factor,aspect ratio,volume fraction,and angle of incidence.Three ML techniques—Artificial Neural Networks,Random Forest,and AdaBoost—were used to train the models.All models demonstrated strong generalization when tested on unseen data.However,AdaBoost outperformed the others with the lowest MAPE(20.1%)and MRD(0.069).Additional analysis on excluded data confirmed the robust predictive abilities and generalization of the proposed model.The models were also evaluated across three flow regimes—Stokes,transitional,and turbulent—to further assess their generalization.A comparative analysis with well-known empirical correlations,such as Haider and Levenspiel and Chien,showed that all ML models outperformed traditional approaches,with AdaBoost achieving the best results.The current work demonstrates that new generated ML techniques can be reliably used to predict drag coefficient of non-spherical particles paving way towards generalization of ML approach.
基金the financial supports from the National Natural Science Foundation of China(grant No.22408394)the Science Foundation of China University of Petroleum-Beijing(grant No.2462021BJRC001).
文摘Biomass energy is considered a promising renewable energy resource to cope with global carbon neutrality goals and the ongoing energy crisis. However, the irregular shapes and varying sizes of milled biomass particles hinder their effective usage in biomass reactors for energy generation. Previous research on non-spherical particles has mainly focused on single-particle systems, with limited studies on binary mixtures. This study employs CFD-DEM method with superquadric shape representation to investigate the mixing behavior of spherical and cylindrical particles in a spouted fluidized bed. The results show that increasing the aspect ratio of cylindrical particles increases accumulation in dead zones. A higher proportion of cylindrical particles significantly reduces spouting height and makes the V-shaped dead zone more evidence. During spouting from a static state, cylindrical particles exhibit notable changes in pitch angle, transitioning from horizontal to vertical orientations, with these trends becoming more pronounced at higher aspect ratios. These findings provide insight into the mixing behavior of binary particle system of spherical and non-spherical particles, and offer a guidance for the reactor operation with these particle types.
基金supported by the National Natural Science Foundation of China(grant No.22078283)China Nuclear Power Operations Co.,Ltd.
文摘This paper introduces a resolved coupling method based on the LBM(Lattice Boltzmann Method) and DEM(Discrete Element Method)for simulating fluid-particle interactions involving non-spherical particles.The super-ellipsoid model is applied so that a wide range of particle shapes can be represented with high accuracy and efficiency,enabling a detailed investigation of shape effects on flow behavior.The proposed method is validated by comparing simulation results with experimental data on the sedimentation of both spherical and non-spherical particles.Then a fluidized bed system containing different kinds of non-spherical particles is studied and the influence of particle shape on the flow field is investigated.The result further confirms the accuracy and robustness of this method in complex multiphase flow systems.Compared to existing LBM-DEM coupling approaches,this study is more accurate and efficient for simulating flow fields involving particles with smooth surfaces,offering a powerful tool for the study of multiphase systems with regular non-spherical particles.
基金the National Natural Science Foundation of China(grant No.U20A20304)financial support from the Fundamental Research Funds for the Central Universities(grant No.FRFCU5710050721).
文摘Gas pulsation is an efficient enhancing way for fluidized bed drying process.In this work,the influence of gas pulsation on mass and heat transfer performance in a fluidized bed with non-spherical wet particles is numerically investigated via the computational fluid dynamics−discrete element method(CFD-DEM)approach,where the liquid transfer between particles and the heat transfer by liquid bridge are considered.The aspect ratio effect of non-spherical particle on drying process is revealed.It is found that the increase of aspect ratio can weaken the overall drying quality.The influence of gas pulsation on the drying of non-spherical particle is analyzed.The results reveal that adjusting a suitable gas pulsation mode can efficiently regulate the drying process of non-spherical wet particles with greater aspect ratios.
文摘Packed bed reactors of non-spherical particles are widely used in chemical industry with the aim to obtain a high active surface area and achieve a homogeneous flow.Despite this,little is known about the arrangement of particles within the bed and the influence of this arrangement on the fluid flow distribution.Magnetic Resonance Imaging (MRI) is a non-invasive tomographic imaging technique that allows 3D visualisation of the packing and flow structure.However,the individual particle information is not obtained using MRI.In this work we investigate different particle detection methods to retrieve the particle position and orientation from MRI images.Results show the successful reconstruction of random packing structures of various non-spherical particle shapes: ellipsoid,spherocylinder,cylinder and cube.The applicability of each method in relation to the particle shape,as well as strengths and drawbacks of each particle detection method are discussed.This paper shows the ability to reconstruct real packed beds of non-spherical particle shapes from MRI images,which opens several research opportunities in the field of chemical engineering.
基金Tianjin Natural Science Foundation for Jingjinji Collaboration,Grant/Award Number:23JCZXJC00240Hebei Natural Science Foundation,Grant/Award Number:H2023201903+2 种基金Beijing Natural Science Foundation,Grant/Award Number:J230006Capital's Funds for Health Improvement and Research,Grant/Award Number:CFH:2022-2-5072CAMS Innovation Fund for Medical Sciences,Grant/Award Number:2021-I2M-1-052。
文摘Background:Sudden sensorineural hearing loss(SSNHL),often associated with tinnitus,significantly impacts individuals'quality of life.Current treatments,such as free drugs via intravenous or intratympanic(IT)administration of dexamethasone(DEX)and lidocaine,face limitations like low bioavailability and rapid drug clearance.To address these challenges,we developed a local co-delivery system combining DEX microcrystals(DEX MCs)and lidocaine-loaded poly(lactic-co-glycolic acid)(PLGA)non-spherical microparticles(LPNMs)for sustained drug release in the inner ear.Methods:DEX MCs and LPNMs were prepared using the traditional precipitation technique and double emulsion-solvent evaporation,respectively.After characterizing physicochemical properties and drug release kinetics,they were dispersed in sodium hyaluronate solution for IT injection,then in vivo pharmacokinetics and biocompatibility in guinea pigs were studied.Results:DEX MCs exhibited stable dissolution,while LPNMs provided sustained lidocaine release,reducing potential side effects.In vivo studies in guinea pigs demonstrated prolonged drug retention in the perilymph and improved pharmacokinetics.Histological evaluation confirmed the good biocompatibility of this combined delivery system,with no significant inner ear damage observed.Conclusion:This co-delivery system can be used as a depot for delivering both DEX and lidocaine to the inner ear and offers a promising approach for the synergistic treatment of SSNHL associated with tinnitus.
基金The authors acknowledge with gratitude the financial support from the National Natural Science Foundation of China （Contract no. 50476082）.
文摘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.
基金The authors express their appreciation to the Science Fund for Creative Research Groups of the National Natural Science Foun-dation of China (No. 51521063)the National Natural Science Foundation of China (No. U1562212)+2 种基金the National Science and Technology Major Project of China (Grant No. 2016ZX05023-006)the National Key Research and Development Program of China (Grant No. 2016YFE0124600)the State Scholarship Fund (CSC file No. 201706440059).
文摘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.
基金This research was financially supported by the National Key Research and Development Program of China(grant No.2019YFC1805605)the National Natural Science Foundation of China(grant No.22078283)。
文摘Screw conveyors are extensively used in modern industry such as metallurgy,architecture and pharmaceutical due to their high-efficiency in the transportation of granular materials.And substantial efforts have been devoted to the study of the screw conveyors.Numerical method is an effective way to study screw conveyor.However,previous studies have mainly focused in the regime of spherical particles while the in-depth investigations for non-spherical particles that should be the most encountered in practical applications are still limited.In view of the above situations,discrete element method(DEM),which has been widely accepted in simulating the discrete systems,is utilized to investigate the conveying process of non-spherical particles in a horizontal screw conveyor,with particles being modeled by super-ellipsoids.In addition,a wear model called SIEM(Shear Impact Energy Model)is incorporated into DEM to predict the wear of screw conveyor.The DEM simulation results demonstrate that the particle shape is influential for the flow behaviors of particles and the wear of conveyor.The conveying performance evaluated quantitatively of both mass flow rate and power consumption is subsequently obtained to investigate the effect of sphericity of particle with different operation parameters.Moreover,particle collision frequency and collision energy consumption are acquired to investigate the possible particle breakage between particles and screw blade.The comparisons between particle-particle collision and particle-wall collision reveal that particles with large shape index have more possibility to be damaged in particle-wall impingement.
文摘We investigated the deposition pattern of microparticles with different particle diameters, shape factors, and initial flow conditions in a realistic human upper respiratory tract model. We identified a close relationship between the deposition fraction and the particle shape factor. The deposition fraction of the particles decreased sharply with increasing particle shape factor because of the decreasing drag force. We also found that the deposition varied at different positions in the upper respiratory tract. At low shape factors, the highest fraction of particles deposited at the mouth and pharynx. However, with increasing shape factor, the deposition fraction in the trachea and lungs increased. Moreover, for a given shape factor, larger particles deposited at the mouth and pharynx, which indicates that the deposition fraction of microparticles in the human upper respiratory tract is affected first and foremost by particle inertia as well as by the drag force.
