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.

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.

scholarly journals Particle Size Distribution Functions at Dust Separation Equipment’s Various Operating Modes

2016 ◽  
Vol 5 (1) ◽  
pp. 41-47 ◽  
Author(s):  
Половченко ◽  
S. Polovchenko ◽  
Веденин ◽  
Evgeniy Vedenin ◽  
Чартий ◽  
...  
Keyword(s):  
Particle Size ◽  
Distribution Function ◽  
Particle Size Distribution ◽  
Human Health ◽  
Size Distribution ◽  
Suspended Particle ◽  
Particle Diameter ◽  
Suspended Particles ◽  
Operating Modes ◽  
The Mean

The size-consist measure is an aerosol particle distribution function (PDF). The suspended particles’ size-consist affects their behavior during the dust separation process, their behavior in the atmosphere, and on the degree of their negative impact on the environment and human health. A numeric parameter allowing recover the particle size distribution function is the mean volumetrically-superficial particle diameter. This diameter changes during the dust separation equipment’s various operating modes. Therefore, the suspended particles’ size-consist control through the mean volumetrically-superficial particle diameter measuring allows determine the most harmful to the environment and human health suspended particle emissions, and more objectively calculate the suspended particle dispersion in the atmosphere.

Informational Measures of the Shape of the Amoroso Distributions for the Research of Dispersed Materials

2021 ◽  
Vol 1031 ◽  
pp. 58-66
Author(s):  
Vitaly Polosin
Keyword(s):  
Particle Size ◽  
Distribution Function ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Applied Research ◽  
Particle Distribution ◽  
Size Distribution Function ◽  
Distribution Model ◽  
Information Uncertainty ◽  
Particle Size Distribution Function

For the particle size distribution function various forms of exponential models are used to construct models of the properties of dispersed substance. The most difficult stage of applied research is to determine the shape of the particle distribution model. For the particle size distribution function various forms of exponential models are used to construct models of the properties of dispersed substance. The most difficult stage of applied research is to determine the shape of the particle distribution model. The article proposes a uniform model for setting the interval of information uncertainty of non-symmetric particle size distributions. Based on the analysis of statistical and information uncertainty intervals, new shape coefficients of distribution models are constructed, these are the entropy coefficients for shifted and non shifted distributions of the Amoroso family. Graphics of dependence of entropy coefficients of non-symmetrical distributions show that distributions well-known are distinguish at small of the shapes parameters. Also it is illustrated for parameters of the form more than 2 that it is preferable to use the entropy coefficients for the unshifted distributions.The material contains also information measures for the well-known logarithmic normal distribution which is a limiting case of distribution Amorozo.

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.

scholarly journals PARTICLE SIZE DISTRIBUTION CORRECTION METHOD USING A SIMULATED ANNEALING TECHNIQUE

2011 ◽  
Vol 10 (1-2) ◽  
pp. 39
Author(s):  
A. N. Diógenes ◽  
L. O. E. dos Santos ◽  
C. P. Fernandes
Keyword(s):  
Particle Size ◽  
Distribution Function ◽  
Simulated Annealing ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Optimization Method ◽  
Correction Method ◽  
Logistic Function ◽  
Three Dimensions ◽  
Circular Particle

The procedure for obtaining the particle size distribution by visual inspection of a sample involves stereological errors, given the cut of the sample. A cut particle, supposedly spherical, with radius R, will be counted as a circular particle with radius r, r≤R. The difference between r and R depends on how far from the center of the sphere the cut was performed. This introduces errors when the extrapolation of the properties from two to three dimensions during the analysis of a sample. The usual method is to correct the distribution by probabilistic functions, which have large errors. This paper presents a method to reduce the error inherent to this problem. The method is to compute a simulation of the preparation process in a sample whose structure can be described by non-penetrating spheres of various diameters which meet a known probability distribution function, for example, a log-logistic function, or even a constant function. For each distribution radius, a number of spheres is generated and virtually cut, generating a bi-dimensional (2D) distribution. The 2D curves of the spheres distribution obtained in this simulation are compared with that obtained by the experimental procedure and then the parameters of the threedimensional distribution function are adjusted until the 2D curves are similar to the experimental one using the optimization method Simulated Annealing for the curve-fitting. In future this method will be applied to the analysis of the oil reservoir rocks.

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