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 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, quantifies two-dimensional distributions of path-integrated Sauter mean diameter, enabling the 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 Sauter mean diameter distributions using the scattering–absorption measurement ratio 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 this work, we present a summary of the various sources of measurement uncertainty in the scattering–absorption measurement ratio diagnostic, like those due to the experimental setup, data processing methods, and theoretical assumptions, and assess how these sources of uncertainty affect the quantified Sauter mean diameter. The spatially resolved Sauter mean diameter measurements that result from the scattering–absorption measurement ratio diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine computational fluid dynamics codes. Careful evaluation and quantification of measurement uncertainties are important to support accurate model validation and to ensure the development of more predictive spray models.