Droplet Size Distribution in Sprays

Mugele, R. A.; Evans, H.

doi:10.1021/ie50498a023

Cited by 559 publications

(215 citation statements)

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“…In equation (4) Mugele & Evans (1951) found the log-normal distribution to produce reasonable approximations to both the number and volume droplet size distribution functions. The Nukiyama & Tanasawa distribution (Nukiyama & Tanasawa, 1939) is also commonly used, but the expression was found to give a good fit to experimental droplet number size distributions but a poor fit to the volume size distributions (Mugele & Evans, 1951).…”

Section: Using the General Gamma Distribution To Represent The Droplementioning

confidence: 97%

“…The Nukiyama & Tanasawa distribution (Nukiyama & Tanasawa, 1939) is also commonly used, but the expression was found to give a good fit to experimental droplet number size distributions but a poor fit to the volume size distributions (Mugele & Evans, 1951). Conversely, the same study found the Rosin & Rammler distribution (Rosin & Rammler, 1933), which is also widely used by scholars, a good fit to experimental droplet volume size distributions but a poor fit to number size distributions.…”

Section: Using the General Gamma Distribution To Represent The Droplementioning

confidence: 99%

“…Boulderston et al (1981) also found that the Rosin-Rammler distribution gave a good fit to their experimental droplet volume size distribution. Other droplet distributions have been mentioned in literature, for example, the chi-square distribution (Hirohasu & Kadota, 1974;Bai & Gosman, 1999), a modified lognormal distribution (Mugele & Evans, 1951), and a modified Rosin-Rammler function (Rizk & Lefebvre, 1985).…”

Section: Using the General Gamma Distribution To Represent The Droplementioning

confidence: 99%

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Using the General Gamma Distribution to Represent the Droplet Size Distribution in a Spray Model

Emekwuru¹

2012

Hydrodynamics - Theory and Model

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Section: Using the General Gamma Distribution To Represent The Droplementioning

confidence: 97%

Section: Using the General Gamma Distribution To Represent The Droplementioning

confidence: 99%

Section: Using the General Gamma Distribution To Represent The Droplementioning

confidence: 99%

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Using the General Gamma Distribution to Represent the Droplet Size Distribution in a Spray Model

Emekwuru¹

2012

Hydrodynamics - Theory and Model

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“…The SMD based on the ratio between the total droplet volume and the total droplet surface area of all the droplets in the polydisperse spray. In general, for the discrete case the mean diameter given by Mugele and Evans (1951) …”

Section: Introductionmentioning

confidence: 99%

Mathematical Modelling of Spray Combustion-Numerical and Analytical Analysis with application to Engineering Science

Nave¹,

Ajadi²,

Gol’dshtein³

2016

APR

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In the present paper we applied two well-known analytical method to the problem of thermal explosion of monodisperse and polydisperse fuel spray. The methods are the method of integral manifold (MIM) and the homotopy analysis method (HAM). The MIM method used as a basic tools for the analysis of SPS system of ordinary differential equations which means that the physical/ mathematical model should contain a small parameter in the governing equations. The HAM is always valid no matter whether there exist small physical parameters or not in contrast to the classical perturbation methods which requires the existence of a small parameter in the system (in general this is not the case). According to the theory of HAM, the convergence and the rate of solution series are dependent on the convergent control parameter ℏ. This means that this parameter gives one a convenient way to adjust and to control the convergent region of the solutions. γ (conventional parameter of Semenov's theory of thermal explosion), the final dimensionless adiabatic temperature of the thermally insulated system after explosion. This parameter is small compared with unity for most gaseous mixture due to the high exothermicity and activation energy of the chemical reactionwhere ϵ d is the emissivity of the droplet surface ϵ 1,2 dimensionless parameters, introduced for the first time (Gol'dshtein, Goldfarb, Shreiber, & Zinoviev, 1996) and describe the relations between the thermo physical properties of the gas and liquid phases

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“…The curves fitted to the measurement data is able to approximate the distribution of the droplet size in a wide range of operation. Among the probability density functions (PDFs), Nukiyama-Tanasawa, Rosin-Rammler, and Gamma are the most frequently used ones in atomization [14,[16][17][18].…”

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confidence: 99%