Evaluation of Vortex Center Location Algorithms for Particle Image Velocimetry Data in an Optical Light-Duty Compression Ignition Engine

2018-01-0209

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
Ever decreasing permitted emission levels and the necessity of more efficient engines demand a better understanding of in-cylinder phenomena. In swirl-supported compression ignition (CI) engines, mean in-cylinder flow structures formed during the intake stroke deeply influence mixture preparation prior to combustion, heat transfer and pollutant oxidation all of which could potentially improve engine performance. Therefore, the ability to characterize these mean flow structures is relevant for achieving performance improvements. CI mean flow structure is mainly described by a precessing vortex. The location of the vortex center is key for the characterization of the flow structure. Consequently, this work aims at evaluating algorithms that allow for the location of the vortex center both, in ensemble-averaged velocity fields and in instantaneous velocity fields. The study is carried out on velocity fields measured using Particle Image Velocimetry (PIV) in an optical light-duty CI engine operated under motored conditions. The algorithms are applied to both ensemble-averaged and instantaneous velocity fields, to evaluate the robustness of the different approaches. When used for instantaneous velocity fields, algorithms based on velocity field’s magnitudes are less robust and might fail to locate the vortex center. On the contrary, an algorithm based on the velocity field topology successfully locate the vortex center location.
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DOI
https://doi.org/10.4271/2018-01-0209
Pages
8
Citation
Pastor, J., Garcia-Oliver, J., Garcia, A., and Pachano, L., "Evaluation of Vortex Center Location Algorithms for Particle Image Velocimetry Data in an Optical Light-Duty Compression Ignition Engine," SAE Technical Paper 2018-01-0209, 2018, https://doi.org/10.4271/2018-01-0209.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0209
Content Type
Technical Paper
Language
English