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Indexed by:期刊论文

Date of Publication:2014-10-01

Journal:INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Included Journals:SCIE、EI

Volume:77

Page Number:173-184

ISSN No.:0017-9310

Key Words:Vaporization; Multi-component droplet; Multi-diffusion; Computational efficiency

Abstract:An improved hybrid multi-component (HMC) vaporization model was developed and applied to predict the vaporization characteristics of a realistic multi-component fuel droplet under various operating conditions in this study. Firstly, the realistic multi-component fuel is modeled as a mixture with a finite number of discrete hydrocarbon classes, and each hydrocarbon class is presented by a probability density function (PDF). Then, an HMC model was constructed based on the recent progress including an improved multi-diffusion sub-model, a corrected formulation for the calculation of Stefan flow velocity, and the temporal variation of thermal physical properties of fuels with temperature and compositions. The predictions of the improved HMC model were validated with the experimental data from literatures for the vaporization of realistic multi-component fuels and satisfactory agreements between the predictions and measurements are achieved. Finally, extensive comparisons of the hybrid multi-component (HMC), continuous multi-component (CMC), and discrete multi-component (DMC) models in the aspects of computational accuracy and efficiency were performed. It is found that the CMC model shows the highest computational efficiency and the lowest accuracy. The DMC model with a large amount of fuel components has the highest accuracy but the lowest efficiency. The HMC model not only could improve the computational efficiency compared with the full DMC model considering all fuel components, but also illustrates significantly better accuracy than the CMC model under the conditions tested in this study. (C) 2014 Elsevier Ltd. All rights reserved.