2017
DOI: 10.1115/1.4037979
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Comparison of Moment-Based Methods for Representing Droplet Size Distributions in Supersonic Nucleating Flows of Steam

Abstract: This paper investigates the performance of moment-based methods and a monodispersed model (Mono) in predicting the droplet size distribution and behavior of wet-steam flows. The studied moment-based methods are a conventional method of moments (MOM) along with its enhanced version using Gaussian quadrature, namely the quadrature method of moments (QMOM). The comparisons of models are based on the results of an Eulerian–Lagrangian (E–L) method, as the benchmark calculations, providing the full spectrum of dropl… Show more

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Cited by 9 publications
(5 citation statements)
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“…To calculate the diameter growth, the critical radius theory [17] is needed to represent the phase transition of all non-equilibrium models. During the phase transition, the process of nucleation and supercritical droplet growth occurs to rebuild the equilibrium.…”
Section: Diameter Prediction and Velocity Calculationmentioning
confidence: 99%
See 1 more Smart Citation
“…To calculate the diameter growth, the critical radius theory [17] is needed to represent the phase transition of all non-equilibrium models. During the phase transition, the process of nucleation and supercritical droplet growth occurs to rebuild the equilibrium.…”
Section: Diameter Prediction and Velocity Calculationmentioning
confidence: 99%
“…The droplet diameter growth is affected by the transfer of heat between the droplet and the surrounding vapor, which has been generalized for a wide range of droplet sizes. The theory [17] is adjusted to the measurement of spray at low pressure.…”
Section: Diameter Prediction and Velocity Calculationmentioning
confidence: 99%
“…More recently Afzalifar et al 22 did further investigations and especially Hughes et al 19 considered the influence of different expansion rates. In line with previous findings the differences between the discrete spectrum method and the monodispersed method are remarkable for high as well as for low expansion velocities.…”
Section: Droplet Size Distribution Modelingmentioning
confidence: 99%
“…Hughes et al [11] studied the spectrum pruning method and QMOM to reduce the droplet groups number. Afzalifar et al [38] found the method of moments only solves several transport equations of droplet sizes which can reduce computational time and QMOM method is a better choose to predict the effect of droplet size distribution.…”
Section: Introductionmentioning
confidence: 99%