Modelling of blended Diesel and biodiesel fuel droplet heating and evaporation

FUEL

卷:187

Article

Al Qubeissi, M.¹  Sazhin, S. S.²  Elwardany, A. E.³ 

[1] Coventry Univ, Sch Mech Aerosp & Automot Engn, Ctr Mobil & Transport, Coventry CV1 2JH, W Midlands, England

[2] Univ Brighton, Sch Comp Engn & Math, Sir Harry Ricardo Labs, Adv Engn Ctr, Brighton BN2 4GJ, E Sussex, England

[3] Univ Alexandria, Fac Engn, Mech Engn Dept, Alexandria 21544, Egypt

关键词: Biodiesel fuel;    Diesel fuel;    Droplet heating;    Fuel blends;    Heating and evaporation;    Multi-component droplets;   

DOI  :  10.1016/j.fuel.2016.09.060

来源: Elsevier

【 摘 要 】

The paper presents a new approach to the modelling of heating and evaporation of dual-fuel droplets with a specific application to blends of biodiesel (represented by the widely used soybean methyl ester, SME) and Diesel fuels in conditions representative of internal combustion engines. The original compositions, with up to 105 components of Diesel and biodiesel fuels, are replaced with a smaller number of components and quasi-components using the recently introduced multi-dimensional quasi-discrete (MDQD) model. Transient diffusion of these components and quasi-components in the liquid phase and temperature gradient and recirculation inside droplets are taken into account. The results are compared with the predictions of the case when blended biodiesel/Diesel fuel droplets are represented by pure biodiesel fuel or pure Diesel fuel droplets. It is shown that droplet evaporation time and surface temperature predicted for 100% SME, representing pure biodiesel fuel, are close to those predicted for pure Diesel fuel. Also, it is shown that the approximations of the actual compositions of B5 (5% SME and 95% Diesel) and B50 (50% SME and 50% Diesel) dual-fuels by 17 quasi-components/components, using the MDQD model, lead to under-predictions in droplet lifetimes by up to 9% and 4%, respectively, under the same engine conditions. The application of the latter model has resulted in above 83% reduction in CPU time compared to the ease when all 105 components are taken into account using the discrete component model. (C) 2016 Elsevier Ltd. All rights reserved.

【 授权许可】

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