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research-article

HIGH-SPEED RAINBOW SCHLIEREN DEFLECTOMETRY OF N-HEPTANE SPRAYS USING A COMMON RAIL DIESEL INJECTOR

[+] Author and Article Information
Eileen M. Mirynowski

Department of Mechanical Engineering University of Alabama Tuscaloosa, AL, USA
emmirynowski@crimson.ua.edu

Ajay K. Agrawal

Department of Mechanical Engineering University of Alabama Tuscaloosa, AL, USA
aagrawal@eng.ua.edu

Joshua A. Bittle

Department of Mechanical Engineering University of Alabama Tuscaloosa, AL, USA
jbittle@eng.ua.edu

1Corresponding author.

ASME doi:10.1115/1.4036959 History: Received February 22, 2017; Revised April 04, 2017

Abstract

More precise measurements of the fuel injection process can enable better combustion control and more accurate predictions resulting in a reduction of fuel consumption and toxic emissions. Many of the current methods researchers are using to investigate the transient liquid fuel sprays are limited by cross sensitivity when studying regions with both liquid and vapor phases present (i.e. upstream of the liquid length). The quantitative rainbow schlieren technique has been demonstrated in the past for gaseous fuel jets and is being developed here to enable study of the spray near the injector. In this work an optically accessible constant pressure flow rig and a modern common rail diesel injector are used to obtain high speed images of vaporizing fuel sprays at elevated ambient temperatures and pressures. Quantitative results of full-field equivalence ratio measurements are presented as well as more traditional measurements such as vapor penetration and angle for a single condition (13 bar, 180°C normal air) using n-heptane injected through a single hole (0.1mm diameter) common rail fuel injector at 1000 bar fuel injection pressure. This work serves as a proof of concept for the rainbow schlieren technique being applied to vaporizing fuel sprays and full details of the image processing routine are provided. The ability of the imaging technique combined with the constant pressure flow rig make this approach ideal for generating large data sets in short periods of time for a wide range of operating conditions.

Copyright (c) 2017 by ASME
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