Title: Measurement of Sauter mean diameter in diesel sprays using a scattering–absorption measurement ratio technique

Abstract

A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path-integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial resolution of the corresponding droplet field. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced and demonstrated in diesel sprays using the Engine Combustion Network Spray D injector, however a more detailed treatment of measurement uncertainties has been needed. In the current work, we present a summary of the various sources of measurement uncertainty in the SAMR diagnostic, like those due to the experimental setup, data processing methods, and theoretical assumptions, andmore » assess how these sources of uncertainty affect the quantified SMD. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. Furthermore, careful evaluation and quantification of measurement uncertainties is important to support accurate model validation and to ensure the development of more predictive spray models.« less

Authors:

Martinez, Gabrielle L.  ^[1];

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Poursadegh, Farzad ^[1]; Magnotti, Gina M. ^[2]; Matusik, Katarzyna E. ^[3]; Duke, Daniel J. ^[3]; Knox, Benjamin W. ^[1]; Kastengren, Alan L. ^[3]; Powell, Christopher F. ^[3]; Genzale, Caroline L. ^[1]

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+ Show Author Affiliations

1. The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
2. The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA, Argonne National Laboratory, Lemont, IL, USA
3. Argonne National Laboratory, Lemont, IL, USA

Publication Date:

Wed Dec 19 00:00:00 EST 2018

Research Org.:

Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Org.:

USDOE Office of Energy Efficiency and Renewable Energy (EERE); U.S. Department of Defense (DOD), Department of the Army. Tank and Automotive Research, Development, and Engineering Center (TARDEC)

OSTI Identifier:

1488343

Alternate Identifier(s):

OSTI ID: 1494666

Grant/Contract Number:  

AC02-06CH11357

Resource Type:

Published Article

Journal Name:

International Journal of Engine Research

Additional Journal Information:

Journal Name: International Journal of Engine Research Journal Volume: 20 Journal Issue: 1; Journal ID: ISSN 1468-0874

Publisher:

SAGE Publications

Country of Publication:

United Kingdom

Language:

English

Subject:

42 ENGINEERING; atomization; diesel; droplet sizing; high-pressure sprays; optical diagnostics