Polytechnic University of Valencia Congress, ILASS2017 - 28th European Conference on Liquid Atomization and Spray Systems

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Quantification of diesel injector dribble using 3D reconstruction from x-ray and DBI imaging
Vitaliy Sechenyh, Jack Turner, Dan Sykes, Daniel J Duke, Andrew B Swantek, Katarzyna E Matusik, Alan Kastengren, Christopher Powell, Alberto Viera, Raul Payri, Cyril Crua

Last modified: 18-07-2017

Abstract


Post-injection dribble is known to lead to incomplete atomisation and combustion due to the release of slowmoving, and often surface-bound, liquid fuel after the end of the injection event. This can have a negative effect on engine emissions, performance, and injector durability. To better quantify this phenomenon we present a new image processing approach to quantify the volume and surface area of ligaments produced during the end of injection, for an ECN ‘Spray B’ 3-hole injector. Circular approximation for cross-sections was used to estimate three-dimensional parameters of droplets and ligaments. The image processing consisted in three stages: edge detection, morphological reconstruction, and 3D reconstruction. For the last stage of 3D reconstruction, smooth surfaces were obtained by computation of the alpha shape which represents a bounding volume enveloping a set of 3D points. The object model was verified by calculation of surface area and volume from 2D images of figures with well-known shapes. We show that the object model fits non-spherical droplets and pseudo-cylindrical ligaments reasonably well. We applied our processing approach to datasets generated by different research groups to decouple the effect of gas temperature and pressure on the fuel dribble process. High-speed X-ray phase-contrast images obtained at room temperature conditions (297 K) at the 7-ID beamline of the Advanced Photon Source at Argonne National Laboratory, together with diffused back-illumination (DBI) images captured at a wide range of temperature conditions (293-900 K) by CMT Motores Térmicos, were analysed and comparedquantitatively.

DOI: http://dx.doi.org/10.4995/ILASS2017.2017.4742


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