A new reduced model for the moments of droplet size distribution in condensing flow

Xiaoke Ku, Rob Hagmeijer

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

Purpose - The purpose of this paper is to create a computationally efficient reduced model (RM) for the moments of droplet size distribution (DSD) in condensing flow. Design/methodology/approach - The kinetic equation (KE) exactly describes the time dependence of the DSD and can be regarded as the most rigorous representation of a system with condensation. Because of the typical wide range in droplet size, the KE requires excessive computational time and is not attractive for most practical applications. To reduce the overall computational efforts, a novel set of moment equations, derived from the KE has been proposed. Findings - To demonstrate the simplicity and accuracy of the model, the authors employ a typical nucleation pulse experiment for which benchmark KE-solutions have also been computed. Comparison of predicted moments from both the RM and the KE approach reveals that the RM is capable of capturing the evolving feature of moments with reasonable accuracy. Originality/value - The authors have created a novel reduced method for numerical computations of the lower-order moments of the DSD in condensing flow. Unlike the typical method of moments, the RM eliminates the need for assumptions on the shape of the distribution function and could estimate the moments at very low computational cost.
Original languageEnglish
Pages (from-to)320-332
Number of pages13
JournalInternational journal of numerical methods for heat & fluid flow
Volume25
Issue number2
DOIs
Publication statusPublished - 2015

Keywords

  • METIS-315342
  • IR-99146

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