CFD Simulation of Spouted Bed Working with a Size Distribution of Sand Particles: Segregation Aspects

2017 ◽  
Vol 899 ◽  
pp. 95-100
Author(s):  
Kássia Graciele dos Santos ◽  
L.V. Ferreira ◽  
Ricardo Correa Santana ◽  
Marcos Antonio de Souza Barrozo
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Cfd Simulation ◽  
Computational Simulation ◽  
Particle Diameter ◽  
Spouted Bed ◽  
Particle Segregation ◽  
Cfd Method ◽  
Mean Particle Diameter

Spouted bed simulations are usually performed using only one granular phase with a mean particle diameter representing the entire particle mixture, instead of a particle size distribution. In this study, the effect of the particle size distribution is accounted through the simulation of a mixture with five granular phases. The results showed that the particle segregation occurs. Larger particles are more concentrated in the upper region, while the smaller particles are preferably positioned in the lower region of the bed. Computational simulation using CFD method reproduced well the segregation experiments with different participle sizes of sand.

Optical Measurement of Gas Turbine Engine Soot Particle Effluents

1998 ◽  
Vol 120 (1) ◽  
pp. 69-76 ◽  
Author(s):  
R. J. Litchford ◽  
F. Sun ◽  
J. D. Few ◽  
J. W. L. Lewis
Keyword(s):  
Particle Size ◽  
Distribution Function ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Gas Turbine ◽  
Soot Particle ◽  
Particle Diameter ◽  
Noise Component ◽  
Multi Wavelength ◽  
Mean Particle Diameter

This paper addresses optical-based techniques for measuring soot particulate loading in the exhaust stream of gas turbine engines. The multi-angle scattering and multi-wavelength extinction of light beams by ensembles of submicrometer soot particles was investigated as a diagnostic means of inferring particle field characteristics. This is, the particle size distribution function and particle number density were deduced using an innovative downhill simplex inversion algorithm for fitting the deconvolved Mie-based scattering/extinction integral to the measured scattering/extinction signals. In this work, the particle size distribution was characterized by the widely accepted two-parameter log-normal distribution function, which is fully defined with the specification of the mean particle diameter and the standard deviation of the distribution. The accuracy and precision of the algorithm were evaluated for soot particle applications by applying the technique to noise-perturbed synthetic data in which the signal noise component is obtained by Monte Carlo sampling of Gaussian distributed experimental errors of 4, 6, and 10 percent. The algorithm was shown to yield results having an inaccuracy of less than 10 percent for the highest noise levels and an imprecision equal to or less than the experimental error. Multi-wavelength extinction experiments with a laboratory bench-top burner yielded a mean particle diameter of 0.039 μm and indicated that molecular absorption by organic vapor-phase molecules in the ultraviolet region should not significantly influence the measurements. A field demonstration test was conducted on one of the JT-12D engines of a Sabre Liner jet aircraft. This experiment yielded mean diameters of 0.040 μm and 0.036 μm and standard deviations of 0.032 μm and 0.001 μm for scattering and extinction methods, respectively. The total particulate mass flow rate at idle was estimated to be 0.54 kg/h.

scholarly journals Digital microscopic image application (DMIA), an automatic method for particle size distribution analysis in waste activated sludge

2021 ◽  
Author(s):  
S. Cazares ◽  
J. A. Barrios ◽  
C. Maya ◽  
G. Velásquez ◽  
M. Pérez ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Activated Sludge ◽  
Size Distribution ◽  
Particle Diameter ◽  
Diffraction Method ◽  
Laser Diffraction ◽  
Waste Activated Sludge ◽  
Equivalent Diameter ◽  
Distribution Analysis

Abstract An important physical property in environmental samples is particle size distribution. Several processes exist to measure particle diameter, including change in electrical resistance, blocking of light, the fractionation of field flow and laser diffraction (these being the most commonly used). However, their use requires expensive and complex equipment. Therefore, a Digital Microscopic Imaging Application (DMIA) method was developed adapting the algorithms used in the Helminth Egg Automatic Detector (HEAD) software coupled with a Neural Network (NN) and Bayesian algorithms. This allowed the determination of particle size distribution in samples of waste activated sludge (WAS), recirculated sludge (RCS), and pretreated sludge (PTS). The recirculation and electro-oxidation pre-treatment processes showed an effect in increasing the degree of solubilization (DS), decreasing particle size and breakage factor with ranges between 44.29%, and 31.89%. Together with a final NN calibration process, it was possible to compare results. For example, the 90th percentile of Equivalent Diameter (ED) value obtained by the DMIA with the corresponding result for the laser diffraction method. DMIA values: 228.76 μm (WAS), 111.18 μm (RCS), and 84.45 μm (PTS). DMIA processing has advantages in terms of reducing complexity, cost and time, and offers an alternative to the laser diffraction method.

Effect Analysis of Various Gradient Particle Size Distribution on Electrical Performance of Anode-Supported SOFCs With Gradient Anode

2020 ◽  
Vol 142 (7) ◽  
Author(s):  
Pei Fu ◽  
Yuansheng Song ◽  
Jian Yang ◽  
Qiuwang Wang
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Current Density ◽  
Molar Fraction ◽  
Particle Diameter ◽  
Electrical Performance ◽  
Diameter Distribution ◽  
Functional Layer ◽  
Layer 2

Abstract Gradient particle size anode has shown great potential in improving the electrical performance of anode-supported solid oxide fuel cells (SOFCs). In this study, a 3D comprehensive model is established to study the effect of various gradient particle size distribution on the cell electrical performance for the anode microstructure optimization. The effect of homogeneous particle size on the cell performance is studied first. The maximum current density of homogeneous anode SOFC is obtained for the comparison with the electrical performance of gradient anode SOFC. Then the effect of various gradient particle size distribution on the cell molar fraction, polarization losses, and electronic current density distribution is analyzed and discussed in detail. Results show that increasing the particle diameter gradient can effectively reduce the anodic concentration overpotential. Decreasing the particle diameter of anode functional layer 2 is beneficial for reducing the activation and ohmic overpotentials. On these bases, the comprehensive electrical performance of SOFCs with gradient particle size anode and homogeneous anode is compared to highlight the optimal gradient particle diameter distribution. In the studied cases of this work, the gradient particle diameter of 0.7 μm, 0.4 μm, and 0.1 μm at anode support layer (ASL), anode functional layer 1, and anode functional layer 2 (case 3) is the optimal particle size distribution.

Estimation of particle size distribution from cross-sectional particle diameter on the cutting plane

2010 ◽  
Vol 21 (6) ◽  
pp. 676-680 ◽  
Author(s):  
Masatoshi Akashi ◽  
Tsukasa Otani ◽  
Atsuko Shimosaka ◽  
Yoshiyuki Shirakawa ◽  
Jusuke Hidaka
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Particle Diameter ◽  
Cutting Plane ◽  
Cross Sectional

Sampling, testing and modeling particle size distribution in urban catch basins

2014 ◽  
Vol 70 (11) ◽  
pp. 1873-1879 ◽  
Author(s):  
G. Garofalo ◽  
M. Carbone ◽  
P. Piro
Keyword(s):  
Particle Size ◽  
Numerical Model ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Particle Diameter ◽  
Experimental Treatment ◽  
Catch Basin ◽  
Traffic Intersection ◽  
Parking Lot ◽  
Catch Basins

The study analyzed the particle size distribution of particulate matter (PM) retained in two catch basins located, respectively, near a parking lot and a traffic intersection with common high levels of traffic activity. Also, the treatment performance of a filter medium was evaluated by laboratory testing. The experimental treatment results and the field data were then used as inputs to a numerical model which described on a qualitative basis the hydrological response of the two catchments draining into each catch basin, respectively, and the quality of treatment provided by the filter during the measured rainfall. The results show that PM concentrations were on average around 300 mg/L (parking lot site) and 400 mg/L (road site) for the 10 rainfall-runoff events observed. PM with a particle diameter of <45 μm represented 40–50% of the total PM mass. The numerical model showed that a catch basin with a filter unit can remove 30 to 40% of the PM load depending on the storm characteristics.

scholarly journals CFD simulation of solids suspension in stirred tanks: Review

2010 ◽  
Vol 64 (5) ◽  
pp. 365-374 ◽  
Author(s):  
Aoyi Ochieng ◽  
Mrice Onyango
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Concentration Distribution ◽  
Cfd Simulation ◽  
Fluid Dynamic ◽  
Cfd Modeling ◽  
Small Scale ◽  
Stirred Tanks ◽  
Solids Concentration

Many chemical reactions are carried out using stirred tanks, and the efficiency of such systems depends on the quality of mixing, which has been a subject of research for many years. For solid-liquid mixing, traditionally the research efforts were geared towards determining mixing features such as off-bottom solid suspension using experimental techniques. In a few studies that focused on the determination of solids concentration distribution, some methods that have been used have not been accurate enough to account for some small scale flow mal-distribution such as the existence of dead zones. The present review shows that computational fluid dynamic (CFD) techniques can be used to simulate mixing features such as solids off-bottom suspension, solids concentration and particle size distribution and cloud height. Information on the effects of particle size and particle size distribution on the solids concentration distribution is still scarce. Advancement of the CFD modeling is towards coupling the physical and kinetic data to capture mixing and reaction at meso- and micro-scales. Solids residence time distribution is important for the design; however, the current CFD models do not predict this parameter. Some advances have been made in recent years to apply CFD simulation to systems that involve fermentation and anaerobic processes. In these systems, complex interaction between the biochemical process and the hydrodynamics is still not well understood. This is one of the areas that still need more attention.

scholarly journals Conductivity prediction of proppant-packs based on particle size distribution under variable stress conditions

2020 ◽  
Vol 205 ◽  
pp. 03010
Author(s):  
Tiancheng Liang ◽  
Jinwei Zhang ◽  
Chuanyou Meng ◽  
Nailing Xiu ◽  
Bo Cai ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Hydraulic Fracturing ◽  
Size Distribution ◽  
Particle Diameter ◽  
Particle Packing ◽  
Stress Conditions ◽  
Sieve Analysis ◽  
Proper Size ◽  
Median Diameter

The conductivity of the proppant-packs is critical in the productivity of hydraulically fractured wells. Proppants are also the best medium for studying particle packing. Sand and ceramic media are two most common proppants used for hydraulic fracturing. This study focuses on investigate the relation between conductivity and properties of proppant-packs, the particle-size distribution, porosity and mean particle diameter have been measured. The porosity of the proppant pack under zero pressure is determined from bulk density and apparent density. To accurately measure the porosity under variable closed stress conditions, the compressed width was taken into consideration. The particle size distribution was measured from sieve analysis. The paper presents results obtained by conducting routine conductivity test on a variety of proppants. The conductivity-porosity relationships are nonlinear. The conductivity is most sensitive to mean grain size, followed by closed stress, and then sorting. Larger median diameter always correlates to higher conductivity at low stress. Loss of conductivity with stress is more severe for large particles sands than small particles. The binomial method can be used to calculate the conductivity of different types and mesh proppants, which is shown to fit conductivity-mean diameter data successfully. The research is of guiding significance to choose the proper size distribution proppants in hydraulic fracturing. Meanwhile, the binomial method is a better predictor of proppant-packs conductivity based on particle size distribution.

The Fundamental Characteristics on Particle Size Distribution of Drilling Rock-Cuttings

2013 ◽  
Vol 275-277 ◽  
pp. 2411-2414 ◽  
Author(s):  
Song Lin Yi ◽  
Zhi Ming Wang ◽  
Xian Zhong Yi ◽  
Wei Chang
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Particle Diameter ◽  
Average Diameter ◽  
Rayleigh Distribution ◽  
Drill Cuttings ◽  
Rock Drill ◽  
Distribution Laws ◽  
Shape Characteristics

The properties of particle size distribution of rock cuttings and its shape characteristics are the most important parameters to petroleum drilling engineering. The samples of rock drill-cuttings are collected from 7 wells within the depths of 3500 m in Liaohe Oilfield of China. The particle size distribution laws of these rock samples with the average diameter over 74 μm are analyzed. The result shows that the drill cuttings feature obvious sheet shape and the size distribution curve of the particles is mainly related to the formation rocks and drilling bits. While drilling at the well depths of between 0 and 2000m by the cone bits, particle size distribution of drill cuttings has a form of approximately power function, the probability particle diameter being 8.50～9.27 mm. Drilling at the depths of between 2000 and 2800 m by the cone bits, the size distribution of cuttings has a form of nearly function, the probability particle diameter being 3.04～4.67 mm. Drilling at the depths under 2800m by PDC bits, the size distribution has a form of nearly the Rayleigh distribution, the probability rock diameter being 0.91～0.94 mm.

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