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Multi-Plane PIV Measurements in a Gasoline Direct Injection Engine
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 15, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The flows in-cylinder have a profound effect on the mixture preparation and subsequent combustion in all engines. These flows are highly three-dimensional in nature and information from multiple planes is required to characterise the flow dynamics. The flow measurements reported here are from three orthogonal planes in an optical access engine that is based on the Jaguar Land Rover AJ200 Gasoline Direct Injection (GDI) engine. Particle Image Velocimetry (PIV) measurements have been taken every 5°CA from the start of induction to the end of compression. Data have been obtained from 300 cycles for separate experiments measuring flows in the tumble plane, the swirl plane and the cross-tumble plane. Vector comparison metrics are used to quantitatively compare ensemble averaged PIV flow fields to Computational Fluid Dynamics (CFD) simulations across each plane in terms of both the velocity magnitude and direction. These quantitative metrics enable identification of regions of interest and differences in flow characteristics across a range of engine operating conditions. Combination of the PIV vector fields from all three planes into composite flow fields enables the interaction between the flows in the three planes to be visualised. During induction the intake jet is visible in all three planes, while the swirl plane measurements show a pair of counter-rotating vortices either side of the intake jet and the tumble plane shows the development of the tumble flow. During compression the center of the tumble vortex traverses the cylinder leading to flow reversal in the swirl and cross tumble measurement planes.
CitationShen, L., Willman, C., Stone, R., Lockyer, T. et al., "Multi-Plane PIV Measurements in a Gasoline Direct Injection Engine," SAE Technical Paper 2020-01-2049, 2020, https://doi.org/10.4271/2020-01-2049.
Data Sets - Support Documents
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