scholarly journals Computer Simulation of Volume Shrinkage after Mixing Container Media Components

1993 ◽  
Vol 118 (6) ◽  
pp. 757-761 ◽  
Author(s):  
Silvia Burés ◽  
Franklin A. Pokorny ◽  
David P. Landau ◽  
Alan M. Ferrenberg
Keyword(s):  
Experimental Data ◽  
Computer Simulation ◽  
Particle Size ◽  
Monte Carlo ◽  
Particle Size Distribution ◽  
Experimental System ◽  
Fine Sand ◽  
Spherical Particles ◽  
Particle Sizes ◽  
Coarse Particles

A FORTRAN computer program was developed to simulate packing of spherical particles via a Monte Carlo procedure. Shrinkage in volume upon mixing different particle sizes was studied and simulated results were compared with experimental data. Maximum experimental shrinkage was obtained when the proportion of coarse particles of pine bark and sand mixtures ranged from 50% to 70% of the volume. Experimental shrinkage of a mixture of coarse and fine sand was closely reproduced by means of simulation. Particle size distribution appears to be the most important factor in relation to shrinkage and also in the establishment of relationships between the simulated and the experimental system.

scholarly journals Particle size distribution of sawdust and wood shavings mixtures

2010 ◽  
Vol 56 (No. 4) ◽  
pp. 154-158 ◽  
Author(s):  
T. Vítěz ◽  
P. Trávníček
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Distribution Function ◽  
Network Analysis ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Mass Fraction ◽  
Particle Sizes ◽  
Wood Shavings ◽  
Number Of Particles

Particle size distribution of the sample of waste sawdust and wood shavings mixtures were made with two commonly used methods of mathematical models by Rosin-Rammler (RR model) and by Gates-Gaudin-Schuhmann (GGS model).On the basis of network analysis distribution function F (d) (mass fraction) and density function f (d) (number of particles captured between two screens) were obtained. Experimental data were evaluated using the RR model and GGS model, both models were compared. Better results were achieved with GGS model, which leads to a more accurate separation of the different particle sizes in order to obtain a better industrial profit of the material.

scholarly journals On soil textural classifications and soil texture-based estimations

2017 ◽  
Author(s):  
Miguel Ángel Martín ◽  
Yakov A. Pachepsky ◽  
Carlos García-Gutiérrez ◽  
Miguel Reyes
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Bulk Density ◽  
Soil Texture ◽  
Fine Sand ◽  
Soil Samples ◽  
Soil Parameters ◽  
Medium Sand ◽  
Texture Representation

Abstract. The soil texture representation with the standard textural fraction triplet 'sand-silt-clay' is commonly used to estimate soil properties. The objective of this work was to test the hypothesis that other fraction sizes in the triplets may provide better representation of soil texture for estimating some soil parameters. We estimated the cumulative particle size distribution and bulk density from entropy-based representation of the textural triplet with experimental data for 6300 soil samples. Results supported the hypothesis. For example, simulated distributions were not significantly different from the original ones in 25 and 85 % of cases when the 'sand-silt-sand' and 'very coarse+coarse + medium sand – fine +very fine sand – silt+clay', were used, respectively. When the same standard and modified triplets were used to estimate the average bulk density, the coefficients of determination were 0.001 and 0.967, respectively. Overall, the textural triplet selection appears to be application- and data-specific.

scholarly journals Monte Carlo simulation of coagulation in discrete particle-size distributions. Part 2. Interparticle forces and the quasi-stationary equilibrium hypothesis

1984 ◽  
Vol 143 ◽  
pp. 387-411 ◽  
Author(s):  
I. A. Valioulis ◽  
E. J. List ◽  
H. J. Pearson
Keyword(s):  
Monte Carlo Simulation ◽  
Particle Size ◽  
Monte Carlo ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Dimensional Analysis ◽  
Spherical Particles ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Coagulation Rate

Hunt (1982) and Friedlander (1960a, b) used dimensional analysis to derive expressions for the steady-state particle-size distribution in aerosols and hydrosols. Their results were supported by the Monte Carlo simulation of a non-interacting coagulating population of suspended spherical particles developed by Pearson, Valioulis & List (1984). Here the realism of the Monte Carlo simulation is improved by accounting for the modification to the coagulation rate caused by van der Waals', electrostatic and hydrodynamic forces acting between particles. The results indicate that the major hypothesis underlying the dimensional reasoning, that is, collisions between particles of similar size are most important in determining the shape of the particle size distribution, is valid only for shear-induced coagulation. It is shown that dimensional analysis cannot, in general, be used to predict equilibrium particle-size distributions, mainly because of the strong dependence of the interparticle force on the absolute and relative size of the interacting particles.

scholarly journals On soil textural classifications and soil-texture-based estimations

Solid Earth ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 159-165 ◽  
Author(s):  
Miguel Ángel Martín ◽  
Yakov A. Pachepsky ◽  
Carlos García-Gutiérrez ◽  
Miguel Reyes
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Bulk Density ◽  
Soil Texture ◽  
Fine Sand ◽  
Soil Samples ◽  
Soil Parameters ◽  
Medium Sand ◽  
Texture Representation

Abstract. The soil texture representation with the standard textural fraction triplet sand–silt–clay is commonly used to estimate soil properties. The objective of this work was to test the hypothesis that other fraction sizes in the triplets may provide a better representation of soil texture for estimating some soil parameters. We estimated the cumulative particle size distribution and bulk density from an entropy-based representation of the textural triplet with experimental data for 6240 soil samples. The results supported the hypothesis. For example, simulated distributions were not significantly different from the original ones in 25 and 85 % of cases when the sand–silt–clay and very coarse+coarse + medium sand − fine + very fine sand − silt+clay were used, respectively. When the same standard and modified triplets were used to estimate the average bulk density, the coefficients of determination were 0.001 and 0.967, respectively. Overall, the textural triplet selection appears to be application and data specific.

scholarly journals Saturated Hydraulic Conductivity and Textural Heterogeneity of Soils

2017 ◽  
Author(s):  
Carlos García-Gutiérrez ◽  
Yakov Pachepsky ◽  
Miguel Ángel Martín
Keyword(s):  
Particle Size ◽  
Hydraulic Conductivity ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Information Entropy ◽  
Fine Sand ◽  
Saturated Hydraulic Conductivity ◽  
Coarse Particles ◽  
Heterogeneity Parameter

Abstract. Saturated hydraulic conductivity Ksat is an important soil parameter that highly depends on soil's particle size distribution (PSD). The nature of this dependency is explored in this work in two ways, (1) by using the Information Entropy as a heterogeneity parameter of the PSD and (2) using descriptions of PSD in forms of textural triplets, different than the usual description in terms of the triplet of sand, silt and clay contents. The power of this parameter, as a descriptor of Ksat and log(Ksat) , was tested on a database of > 19 K soils. We found coefficients of determination of up to 0.977 for log(Ksat) using a triplet that combines very coarse, coarse, medium and fine sand as coarse particles, very fine sand as intermediate particles, and silt and clay as fines. The power of the correlation is analysed for different textural classes and different triplets. Overall, the use of textural triplets different than traditional, combined with IE, may provide a useful tool for predicting Ksat values.

scholarly journals Contribution of Fine Particles to Air Emission at Different Phases of Biomass Burning

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 278 ◽  
Author(s):  
Niloofar Ordou ◽  
Igor E. Agranovski
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Fine Particles ◽  
Combustion Process ◽  
Coarse Particles ◽  
Biomass Smoke ◽  
Smoke Particles ◽  
Air Emission ◽  
Entire Duration ◽  
Diffusion Properties

Particle size distribution in biomass smoke was observed for different burning phases, including flaming and smouldering, during the combustion of nine common Australian vegetation representatives. Smoke particles generated during the smouldering phase of combustions were found to be coarser as compared to flaming aerosols for all hard species. In contrast, for leafy species, this trend was inversed. In addition, the combustion process was investigated over the entire duration of burning by acquiring data with one second time resolution for all nine species. Particles were separately characterised in two categories: fine particles with dominating diffusion properties measurable with diffusion-based instruments (Dp < 200 nm), and coarse particles with dominating inertia (Dp > 200 nm). It was found that fine particles contribute to more than 90 percent of the total fresh smoke particles for all investigated species.

Effects of Multiple Impacts and Size Distribution of Particles on Erosion Predictions Using CFD

2007 ◽  
Author(s):  
Yongli Zhang ◽  
Brenton S. McLaury ◽  
Siamack A. Shirzai
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Target Material ◽  
Average Particle ◽  
Multiple Impacts ◽  
Cfd Simulations ◽  
Erosion Damage ◽  
Wide Range

Erosion equations are usually obtained from experiments by impacting solid particles entrained in a gas or liquid on a target material. The erosion equations are utilized in CFD (Computational Fluid Dynamics) models to predict erosion damage caused by solid particle impingements. Many erosion equations are provided in terms of an erosion ratio. By definition, the erosion ratio is the mass loss of target material divided by the mass of impacting particles. The mass of impacting particles is the summation of (particle mass × number of impacts) of each particle. In erosion experiments conducted to determine erosion equations, some particles may impact the target wall many times and some other particles may not impact the target at all. Therefore, the experimental data may not reflect the actual erosion ratio because the mass of the sand that is used to run the experiments is assumed to be the mass of the impacting particles. CFD and particle trajectory simulations are applied in the present work to study effects of multiple impacts on developing erosion ratio equations. The erosion equation as well as the CFD-based erosion modeling procedure is validated against a variety of experimental data. The results show that the effect of multiple impacts is negligible in air cases. In water cases, however, this effect needs to be accounted for especially for small particles. This makes it impractical to develop erosion ratio equations from experimental data obtained for tests with sand in water or dense gases. Many factors affecting erosion damage are accounted for in various erosion equations. In addition to some well-studied parameters such as particle impacting speed and impacting angle, particle size also plays a significant role in the erosion process. An average particle size is usually used in analyzing experimental data or estimating erosion damage cases of practical interest. In petroleum production applications, however, the size of sand particles that are entrained in produced fluids can vary over a fairly broad range. CFD simulations are also performed to study the effect of particle size distribution. In CFD simulations, particle sizes are normally distributed with the mean equaling the average size of interest and the standard deviation varying over a wide range. Based on CFD simulations, an equation is developed and can be applied to account for the effect of the particle size distribution on erosion prediction for gases and liquids.

scholarly journals Monte Carlo simulation for soot dynamics

2012 ◽  
Vol 16 (5) ◽  
pp. 1391-1394 ◽  
Author(s):  
Kun Zhou
Keyword(s):  
Particle Size ◽  
Monte Carlo ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Gas Phase ◽  
Volume Fraction ◽  
Soot Formation ◽  
Bimodal Distribution ◽  
Number Density ◽  
Stochastic Error

A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

scholarly journals Theoretical and Experimental Evaluation of Particle size Effect of Iron , Cobalt ,and Nickel Powders Suspended in Al Dura oil on XRF Intensities

2007 ◽  
Vol 4 (3) ◽  
pp. 475-481
Author(s):  
Baghdad Science Journal
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Laser System ◽  
Particle Size Effect ◽  
Particle Sizes ◽  
Iron Cobalt ◽  
X Ray ◽  
Nickel Powders ◽  
Good Agreement ◽  
Cobalt And Nickel

Iron , Cobalt , and Nickel powders with different particle sizes were subjected to sieving and He-Ne laser system to determine the particle size . 1wt% from each powders was blended carefully with 99wt% from Iraqi oil . Microscopic examination were carried for all samples to reveal the particle size distribution . A Siemens type SRS sequential wavelength dispersive(WDS) X-ray spectrometer was used to analyze all samples , and the XRF intensity were determined experimentally and theoretically for all suspended samples , Good agreement between theoretical and experimental results were found .

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