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Title: Measurement of Sauter Mean Diameter (SMD) in Diesel Sprays Using a Scattering-Absorption Measurement Ratio (SAMR) Technique

Conference ·
OSTI ID:1785890

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 and temporal 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, and 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. Careful evaluation and quantification of measurement uncertainties is important to support accurate model validation and to ensure the development of more predictive spray models.

Research Organization:
Georgia Tech Research Corporation (Georgia Institute of Technology)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Contributing Organization:
Argonne National Lab
DOE Contract Number:
EE0007333
OSTI ID:
1785890
Report Number(s):
DOE-GATECH-7333
Resource Relation:
Conference: Conference on Thermo- and Fluid Dynamic Processes in Direct Injection Engines (THIESEL), Valencia Spain, 2018
Country of Publication:
United States
Language:
English