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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Applied Energyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Applied Energy
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Analysis of spray combustion characteristics of diesel, biodiesel and their n-pentanol blends based on a one-dimensional semi-phenomenological model

Authors: Yu Liu; Zhipeng Yuan; Yinjie Ma; Jianqin Fu; Ronghua Huang; Jingping Liu;

Analysis of spray combustion characteristics of diesel, biodiesel and their n-pentanol blends based on a one-dimensional semi-phenomenological model

Abstract

Abstract Spray mixing and combustion processes are regarded as the major factors that determine the energy conversion efficiency and emission level of internal combustion engines. However, the related researches mainly rely on 3D flow simulation or optical engine experiments, which are highly expensive and time-consuming. In order to provide a more convenient solution, this paper developed a one-dimensional semi-phenomenological model to achieve accurate and efficient predictions on spray combustion characteristics. The model was constructed by a dimensionless spray theoretical model and limited experimental data of macroscopic spray characteristics. Inside the proposed model, a physical module was used to physical module spray air-fuel mixing conditions like fuel distribution and evaporation. Besides, an improved Arrhenius-typed correlation concerning injection parameters and environment variables was introduced to describe the chemical ignition characteristic of spray combustion. The optical experiment results showed that this method is simple and effective, and the forecasting is satisfactory. Based on the new model, the influences of blending n-pentanol on the spray combustion characteristics of diesel and biodiesel were investigated. On the physical aspect, the critical fuel concentration at liquid length position decreases with n-pentanol is blended into both fuels in the most cases, but witnessed a significant leap in 1200 K condition, especially for diesel blends; the physical ignition delay times of both diesel and biodiesel blends decreases first and go up later. On the chemical aspect, the join of n-pentanol caused the gap between the physical delay time and the chemical delay time much narrower, but the ignition patterns were different in diesel blends and biodiesel blends. Moreover, this paper proposed a series of correlations focused on the liquid length and ignition delay of n-pentanol blends sprays. These correlations covered wide conditions and showed better prediction accuracy than traditional ones.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%