Spray Characterization and Turbulence Properties in an Isothermal Spray With Swirl

1990 ◽  
Vol 112 (1) ◽  
pp. 60-66 ◽  
Author(s):  
A. Bren˜a de la Rosa ◽  
W. D. Bachalo ◽  
R. C. Rudoff
Keyword(s):  
Dynamic Behavior ◽  
Radial Distribution ◽  
Particle Number ◽  
Swirling Flow ◽  
Particle Number Density ◽  
Recirculation Region ◽  
Liquid Volume ◽  
Volume Flux ◽  
Number Density ◽  
Mean Velocity

The present work reports an experimental study of the effect of swirl on the dynamic behavior of drops and on the velocity and turbulence fields of an isothermal spray using a two-component Phase Doppler Particle Analyzer (PDPA). It represents the first phase of an effort to investigate the effect of swirl on the structure of liquid spray flames, the stability of the flame, and its effect on the emission of pollutants. A vane-type swirler was placed on the liquid supply tube of a pressure atomizer and tested in the wind tunnel under specified conditions. Mean velocity and turbulence properties were obtained for the gas phase. In addition, drop velocity and drop size distributions, particle number densities, and volume flux were measured at different locations within the swirling flow. Large differences in the spatial distribution of the drops over its size, velocity, and number density are observed when the spray in coflowing air with the same axial velocity is compared with the atomizer spraying into the swirling flow field. Large drops seem to be recirculated into the core of the swirling flow, while rather small drops surround this central region. The radial distribution of particle number density and the liquid volume flux are also different when the atomizer spraying into the coflowing air and into the swirling field are compared. Particle number densities for the latter exhibit higher peak values close to the nozzle; but show almost the same peak values as in the coflowing case but at a different radial location further downstream. The velocity of specific drop sizes was also obtained. Drops as large as 5μm are seen to follow closely the mean velocity of the gas. The turbulence properties of the swirling flow show significant influence on the dynamic behavior of the drops. Radial distributions of turbulence kinetic energy, normal Reynolds stresses, and Reynolds shear stresses exhibit double peak values, which delineate the boundaries of the central recirculation region and the external free stream. Within these boundaries the radial distribution of both particle number density and volume flux are seen to attain their maximum values.

scholarly journals Spray Characterization and Turbulence Properties in an Isothermal Spray With Swirl

1989 ◽  
Author(s):  
A. Breña De La Rosa ◽  
W. D. Bachalo ◽  
R. C. Rudoff
Keyword(s):  
Dynamic Behavior ◽  
Radial Distribution ◽  
Particle Number ◽  
Swirling Flow ◽  
Particle Number Density ◽  
Recirculation Region ◽  
Liquid Volume ◽  
Volume Flux ◽  
Number Density ◽  
Mean Velocity

The present work reports an experimental study of the effect of swirl on the dynamic behavior of drops and on the velocity and turbulence fields of an isothermal spray using a two-component Phase Doppler Particle Analyzer (PDPA). It represents the first phase of an effort to investigate the effect of swirl on the structure of liquid spray flames, the stability of the flame, and its effect on the emission of pollutants. A vane type swirler was placed on the liquid supply tube of a pressure atomizer and tested in the wind tunnel under specified conditions. Mean velocity and turbulence properties were obtained for the gas phase. In addition, drop velocity and drop size distributions, particle number densities, and volume flux were measured at different locations within the swirling flow. Large differences in the spatial distribution of the drops over its size, velocity, and number density are observed when the spray in a co-flowing air with the same axial velocity is compared with the atomizer spraying into the swirling flow field. Large drops seem to be recirculated into the core of the swirling flow, while rather small drops surround this central region. The radial distribution of particle number density and liquid volume flux are also different when the atomizer spraying into the co-flowing air and into the swirling field are compared. Particle number densities for the latter exhibit higher peak values close to the nozzle but show almost the same peak values as the quiescent spray but at different radial location further downstream. The velocity of specific drop sizes was also obtained. Drops as large as 5 μm are seen to follow closely the mean velocity of the gas. The turbulence properties of the swirling flow show significant influence on the dynamic behavior of the drops. Radial distribution of turbulence kinetic energy, normal Reynolds stresses, and Reynolds shear stresses exhibit double peak values which delineate the boundaries of the central recirculation region and the external free stream. Within these boundaries the radial distribution of both particle number density and volume flux are seen to attain their maximum values.

scholarly journals Diagnostics Development for Spray Characterization in Complex Turbulent Flows

1988 ◽  
Author(s):  
W. D. Bachalo ◽  
A. Brẽna De La Rosa ◽  
R. C. Rudoff
Keyword(s):  
Turbulent Flows ◽  
Mass Flux ◽  
Gas Turbines ◽  
Particle Number ◽  
Sample Volume ◽  
Particle Number Density ◽  
Accurate Estimation ◽  
Volume Flux ◽  
Number Density ◽  
Factors Affecting

The present work reports a detailed investigation of air-liquid interaction in sprays along with particle number density and mass flux measurements in complex turbulent flows such as those present in gas turbines and rocket combustors. Data have been obtained for the characterization of sprays in complex flows which include detailed drop size and drop velocity distributions, size-velocity correlations, mass flux, and particle number density. Key factors affecting the measurement of the sample volume size are discussed in detail since an accurate estimation of it is essential to the particle number density and volume flux determined by the instrument. The discrimination of refraction and reflective scattering components and their influence on the measurements is also discussed. Data comparing the phase Doppler results to alternate methods of measuring number density and volume flux are also presented. These results showed agreement to within 15% in most cases for realistic flow configurations.

Experimentally determined particle number density statistics in an industrial-scale, pulverized-coal-fired boiler

1993 ◽  
Vol 7 (6) ◽  
pp. 842-851 ◽  
Author(s):  
M. Queiroz ◽  
M. P. Bonin ◽  
J. S. Shirolkar ◽  
R. W. Dawson
Keyword(s):  
Particle Number ◽  
Particle Number Density ◽  
Pulverized Coal ◽  
Industrial Scale ◽  
Number Density

The next step in precipitation polymerization of N-isopropylacrylamide: particle number density control by monochain globule surface charge modulation

2016 ◽  
Vol 7 (32) ◽  
pp. 5123-5131 ◽  
Author(s):  
O. L. J. Virtanen ◽  
M. Brugnoni ◽  
M. Kather ◽  
A. Pich ◽  
W. Richtering
Keyword(s):  
Particle Size ◽  
Robust Control ◽  
Surface Charge ◽  
Particle Number ◽  
Particle Number Density ◽  
Precipitation Polymerization ◽  
Number Density ◽  
Density Control ◽  
Charge Modulation

Many applications of poly(N-isopropylacrylamide) microgels necessitate robust control over particle size.

Effect of Particle Number Density on Wave Dispersion in a Two-Dimensional Yukawa System

2017 ◽  
Vol 34 (7) ◽  
pp. 075203
Author(s):  
Rang-Yue Zhang ◽  
Yan-Hong Liu ◽  
Feng Huang ◽  
Zhao-Yang Chen ◽  
Chun-Yan Li
Keyword(s):  
Particle Number ◽  
Wave Dispersion ◽  
Particle Number Density ◽  
Two Dimensional ◽  
Number Density

Simulation of Multi-Phase Glass-Melt Flows in a Glass Melter

2001 ◽  
Author(s):  
S. L. Chang ◽  
C. Q. Zhou ◽  
B. Golchert ◽  
M. Petrick
Keyword(s):  
Heat Transfer ◽  
Molten Glass ◽  
Transfer Rate ◽  
Liquid Glass ◽  
Particle Number ◽  
Particle Number Density ◽  
Number Density ◽  
Melt Flow ◽  
Glass Melter ◽  
Multi Phase

Abstract A typical glass furnace consists of a combustion space and a melter. The intense heat, generated from the combustion of fuel and air/oxygen in the combustion space, is transferred mainly by radiation to the melter where the melt sand and cullet (scrap glass) are melted, creating molten glass. The melter flow is a complex multi-phase flow including solid batches of sand/cullet and molten glass. Proper modeling of the flow patterns of the solid batch and liquid glass is a key to determining the glass quality and furnace efficiency. A multi-phase CFD code has been developed to simulate glass melter flow. It uses an Eulerian approach for both the solid batch and the liquid glass-melt flows. The mass, momentum, and energy conservation equations of the batch flow are used to solve for local batch particle number density, velocity, and temperature. In a similar manner, the conservation equations of mass, momentum, and energy of the glass-melt flow are used to solve for local liquid molten glass pressure, velocity, and temperature. The solid batch is melted on the top by the heat from the combustion space and from below by heat from the glass-melt flow. The heat transfer rate from the combustion space is calculated from a radiation model calculation while the heat transfer rate from the glass-melt flow to the solid batch is calculated from a model based on local particle number density and glass-melt temperature. Energy and mass are balanced between the batch and the glass-melt. Batch coverage is determined from local particle number density and velocity. A commercial-scale glass melter has been simulated at different operating/design conditions.

scholarly journals Diffusion of Particles, Heat and Magnetic Fields in Compressible Turbulent Media

1991 ◽  
Vol 130 ◽  
pp. 71-74
Author(s):  
A.Z. Dolginov ◽  
N.A. Silant’ev
Keyword(s):  
Magnetic Field ◽  
Magnetic Fields ◽  
Vector Fields ◽  
Particle Number ◽  
Particle Number Density ◽  
Turbulent Diffusivity ◽  
Number Density ◽  
Scalar And Vector Fields ◽  
Kinetic Coefficients ◽  
The Magnetic Field

AbstractA new method for the calculation of kinetic coefficients is presented. This method allows us to obtain the distribution of scalar and vector fields (such as the temperature, the admixture particle number density and the magnetic field) in turbulent cosmic media with any value of S = u0т0/R0. The explicit expression for the “turbulent” diffusivity DT is obtained. In some cases DT becomes negative, implying the clustering of the admixture particles in patches (a local increase of the temperature and magnetic fields). The magnetic α-effect is considered for the case S ~ 1.

Particle Deposition in a Room-Scale Chamber With Particle Injection

2005 ◽  
Author(s):  
N. Zhang ◽  
Z. Charlie Zheng ◽  
L. Glasgow ◽  
B. Braley
Keyword(s):  
Particle Deposition ◽  
Particle Number ◽  
Particle Distribution ◽  
Turbulent Transport ◽  
Distribution Patterns ◽  
Particle Number Density ◽  
Number Density ◽  
Small Particles ◽  
Particle Injection ◽  
Simulation Results

A model simulating the deposition of small particles with turbulent transport, sedimentation, and coagulation, is presented. Experimental measurements were conducted in a room-scale chamber using a specially designed sequential sampler. The measured deposition-rate data are compared with the simulation results. Distributions of particle-number density at different times are plotted in several viewing planes to facilitate discussion of the particle distribution patterns.

The Dependence of Pool Scrubbing Decontamination Factor on Particle Number Density: Modeling Based on Bubble Mass and Energy Balance

2020 ◽  
Author(s):  
Yasuteru Sibamoto ◽  
Haomin Sun ◽  
Yoshiyasu Hirose ◽  
Yutaka Kukita
Keyword(s):  
Energy Balance ◽  
Particle Number ◽  
Sharp Decrease ◽  
Particle Growth ◽  
Decontamination Factor ◽  
Particle Number Density ◽  
Vapor Condensation ◽  
Vapor Concentration ◽  
Number Density ◽  
Condensational Growth

Abstract The dependence of pool scrubbing performance on particle number density is studied through numerical simulation of experimental results. The DF values obtained from the authors’ experiments (Sun et al., Sci. Technol. Nucl. Inst., Article ID 1743982, 2019) indicate a sharp decrease with an increase in the inlet particle number density beyond 1011/m3. The mechanisms underlying such dependence is yet to be studied. In this paper, a simple model is developed to study the factors affecting the experimentally observed dependence of DF. The test results suggest that the condensational growth of particles plays an essential role in the inertial capture. The vapor condensation on the particles has an effect to deplete the vapor supersaturation in the bubble by both lowering the vapor concentration and raising the temperature. This effect will become important at high particle number densities. The bubble mass and energy balance is calculated to derive the particle growth and the inertial DF as a function of the bubble rise distance through the pool water. The balance is assumed to be quasi-steady, and the vapor concentration and the temperature to be uniform in the bubble. It is shown that the model reproduces the tendency observed in the experimental DF. The model predicts that the degree of supersaturation is affected when particle concentration exceeds 1011/m3, curbing the condensational growth of particles, and thereby retarding the inertial capture.

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