Droplet size and morphology characterization for dense sprays by image processing: application to the Diesel spray

Droplet size and morphology characterization for dense sprays by image processing: application to... Up to now, measurement of drop size remains difficult in dense sprays such as those encountered in Diesel applications. Commonly used diagnostics are often limited due to multi-scattering effects, high drop velocity and concentration and also nonspherical shapes. The advantage of image-based techniques on the others is its ability to describe the shape of liquid particles that are not fully atomized or relaxed. In the present study, a model is developed to correct the main drawbacks of imaging. It permits to define criteria for the correction of the apparent size of an unfocused drop and to determine a measurement volume independent of the drop size. This considerably reduces the over-estimation of large drops in the drop size distribution. Drop shapes are also characterized by four morphological parameters. The image-based granulometer is satisfactorily compared to a PDPA and a diffraction-based granulometer for measurements on an ultrasonic spray. Then, the new granulometer is applied to a diesel spray. One of the results of the analysis is that even if mean drop size distributions are stable 30 mm downstream from the nozzle outlet, the shape of the drops is still evolving towards the spherical shape. The atomization process is thus not totally established at this position in opposition to what can be deduced from the drop size distribution alone. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

Droplet size and morphology characterization for dense sprays by image processing: application to the Diesel spray

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Copyright © 2005 by Springer-Verlag
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
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