The Effects of the Particle Size Ratio on the Behaviors of Binary Granular Materials

The particle size ratio(PSR)is an important parameter for binary granular materials,which may aect the microstructure and macro behaviors of granular materials.However,the eect of particle ratio on granular assemblies with dierent arrangements is still unclear.To explore and further clarify the eect of PSR in dierent packing structures,three types of numerical samples with regular,layered,and random packing are designed.Numerical results show that PSR has signi􀀀cant eects on binary granular samples with regular packing.The larger the PSR,the stronger the strength,the larger the modulus,and the smaller the angle between the shear band and the load direction.And a theoretical solution of the peak stress ratio vs.PSR is obtained for regular packing,and the results by DEM are in good agreement with the theoretical solution.Under layered packing,PSR has little eect on peak stress ratio due to similar microstructure obtained with the changing of PSR.The modulus slightly increased with the increase of PSR.Under random packing with small grain content of 50%,PSR has little eect in the range of 0.5–0.9,but in a larger range,larger PSR leads to greater modulus.

Studying the particle size ratio effect on granular mixing in a vertically vibrated bed of two particle types

The uniform mixing of solids is important in many industries,such as the pharmaceutical,food,petrochemical and chemical industries.We numerically investigated the effect of particle size ratio on the mixing of bisized particles in a quasi-two-dimensional vibrationally fluidized bed.The granular bin ary mixtures comprised spherical particles with different size ratios.Three-dimensional discrete-element simulations agreed with previous experimental results.Convective and diffusive mechanisms occurred Keywords:Discrete-element modeling Fluidization Granular media Mixing Particle size ratio Vibration within the vibrated bed.The particle size had no significant influence on convective mixing,whereas the diffusive mechanism strengthened for large size ratios.The average particle velocity was larger in a mixture of large size ratios.The stronger diffusive motion and larger average particle velocity caused the particles to mix faster for large size ratios.The final mixing index decreased with size ratio because of the difference between the size and number of small and large particles.

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

Investigation of fluid flow-induced particle migration in granular filters using a DEM-CFD method

In embankments and earth dams, the granular filter used to protect the base soil from being eroded by the fluid flow is a major safety device. In this paper, the migration mechanism of the base soil through this type of filters with a fluid flow in the base soil-filter system is studied by using the coupled distinct element method and computational fluid dynamics（DEM-CFD） model. The time-dependent variations of the system parameters such as the total eroded base soil mass, the distribution of the eroded particles within the filter, the porosity, the pore water pressure, and the flow discharge are obtained and analyzed. The conceptions of the trapped particle and the trapped ratio are proposed in order to evaluate the trapped condition of the base soil particles in the filter. The variation of the trapped ratio with time is also analyzed. The results show that the time evolutions of the parameters mentioned above are directly related to the gradation of the filter, which is defined as the representative particle size ratio of the base soil to the filter using an empirical filter design criterion. The feasibility of the model is validated by comparing the numerical results with some experimental and numerical results.

Discrete element modeling of the effect of particle size distribution on the small strain stiffness of granular soils

Discrete element modeling was used to investigate the effect of particle size distribution on the small strain shear stiffness of granular soils and explore the fundamental mechanism controlling this small strain shear stiffness at the particle level. The results indicate that the mean particle size has a negligible effect on the small strain shear modulus. The observed increase of the shear modulus with increasing particle size is caused by a scale effect. It is suggested that the ratio of sample size to the mean particle size should be larger than 11.5 to avoid this possible scale effect. At the same confining pressure and void ratio, the small strain shear modulus decreases as the coefficient of uniformity of the soil increases. The Poisson＇s ratio decreases with decreasing void ratio and increasing confining pressure instead of being constant as is commonly assumed. Microscopic analyses indicate that the small strain shear stiffness and Poisson＇s ratio depend uniquely on the soil＇s coordination number.

Polymeric microsphere injection in large pore-size porous media

High water-cut has become a worldwide challenge for oil production.It requires extensive efforts to process and dispose.This entails expanding water handling facilities and incurring high power consumption costs.Polymeric microsphere injection is a cost-effective way to deal with excessive water production from subterranean formations.This study reports a laboratory investigation on polymeric microsphere injection in a large volume to identify its in-depth fluid diversion capacity in a porous media with large pore/particle size ratio.The performance of polymeric microsphere injection was evaluated using etched glass micromodels based on the pore network of a natural carbonate rock,which were treated as water-wet or oil-wet micromodels.Waterflooding was conducted to displace oil at reservoir temperature of 95°C,followed by one pore volume of polymeric microsphere injection.Three polymeric microsphere samples with median particle size of 0.05,0.3,and 20μm were used to investigate the impact of particle size of the polymeric microspheres on incremental oil production capacity.Although the polymeric microspheres were much smaller than the pores,additional oil production was observed.The incremental oil production increased with increasing polymeric microsphere concentration and particle size.As a comparison,polymeric microsphere solutions were injected into oil-wet and water-wet micromodels after waterflooding.It was observed that the oil production in oil-wet micromodel was much higher than that in water-wet micromodel.The wettability of micromodels affected the distribution patterns of the remaining oil after waterflooding and further dominated the performance of the microsphere injection.The study supports the applicability of microsphere injection in oil-wet heterogeneous carbonates.

An insight into the mechanical behavior of binary granular soils

This paper investigates the participation of the fines fraction in the load-carrying structure of binary mixtures of granular soils. For this purpose, various fractions of two fine sands were added to two coarse sands with the same particle size distribution, but different particle shape characteristics. Based on the results of 144 direct shear tests, it was found that fines participation in the load-bearing structure increases with fines content. At the same fines content, the participation of the fines in the load-carrying structure of loose mixtures is greater than in samples that were initially compacted. In addition, it was observed that fines participation rises with the increase in the average size of the fines fraction.

Experimental study on the 3D vibrated packing densification of binary sphere mixtures

The packing densification of binary spherical mixtures under 3D mechanical vibration was studied experimentally. The influences of vibration frequency （ω）, volume fraction of large spheres （XL）, sphere size ratio （r, diameter ratio of small to large spheres）, and container size （D） on the random binary packing density （p） were systematically analyzed. For any given set of conditions, there exist optimal ω and XL to realize the densest random binary packing; too large or small ω and XL is not helpful for densification. The influences of both r and D on p are monotonic; either reducing r or increasing D leads to a high value of p. With all other parameters held constant, the densest random packing occurs when XL is dominant, which is in good agreement with the Furnas relation. Moreover, the highest random binary packing density obtained in our work agrees well with corresponding numerical and analytical results in the literature.