Multi-plane time-resolved Particle Image Velocimetry (PIV) flow field measurements in an optical Spark-Ignition Direct-Injection (SIDI) engine for Large-Eddy Simulation (LES) model validations

Abstract

In-cylinder flow characteristics play a significant role in the fuel–air mixing process of Spark-Ignition Direct-Injection (SIDI) engines. Typically, planar Particle Image Velocimetry (PIV) is used to measure a representative velocity field sectioning through the center plane of the engine cylinder. However, a single flow field offers very limited perspective regarding the Three-Dimensional nature of the flow fields. Since the in-cylinder flow is stochastically complex, large datasets of flow field measurements along multiple planes are needed to provide a complete panoramic understanding of the flow dynamics. In this study, a high-speed PIV is applied to measure the crank-angle resolved flow fields inside a single-cylinder four-valve optical SIDI engine. Five flow fields along different tumble planes are captured. These five planes include two orthogonal planes cutting through the spark plug tip, two parallel planes sectioning through middle point of the intake and exhaust valves, and one plane through the centers of two intake valves. In addition, numerical computations are carried out with Large-Eddy Simulation (LES) model in CONVERGE. With the guidance from multi-plane PIV measurements, a novel validation approach is proposed in this study. The quantitative analysis and comparison between LES simulations and PIV experiments are divided in terms of global and local comparison indices. The global comparison indices provide a quantitative single value to quickly check the overall similarity of velocity directions and magnitudes between PIV and LES results of a specific individual plane. The local comparison indices further evaluate the similarity between the flow fields of LES and PIV point by point to identify any dissimilar regions and vortex features, which are likely to indicate the complex flow structures at low-speed regions. In summary, not only can the combined data analysis approach provide a reliable way for LES model validations, it can also reveal the physical quantifications of the complex in-cylinder flow characteristics.

On the use of particle image velocimetry (PIV) data for the validation of Reynolds averaged Navier-Stokes (RANS) simulations during the intake process of a spark ignition direct injection (SIDI) engine

“…By first re-arranging the vector fields p and q into column vectors, this application of the relevance index returns a single scalar value for the whole-field comparison of two vector fields. If the spatial variation in local ‘quality of alignment’ across the field is of interest, an alternative approach is to perform a point-by-point comparison by calculating the RI value separately at each spatial coordinate, returning a spatially-resolved ‘alignment quality’ field result 50 (equivalent to the Local Structure Index, LSI 51 ). At each coordinate, the input vectors for equation (1) would be the individual vectors at the corresponding location within each field.…”

Manifold reduction techniques for the comparison of crank angle-resolved particle image velocimetry (PIV) data and Reynolds-averaged Navier-Stokes (RANS) simulations in a spark ignition direct injection (SIDI) engine

“…It would be useful, on the other hand, to have spatial information about how well the two flow fields are aligned and where the major differences occur. To achieve this, Chen et al 41 and Zhao et al 42 extended the idea of RI to point-to-point comparisons, and Zhao et al termed it as the Local Structure Index (LSI):…”

Quantitative metrics for comparison of in-cylinder velocity fields using particle image velocimetry

“…This metric has been used to investigate the convergence of simulated OH mass fraction and soot mass fraction distributions of an n-dodecane spray flame (Ameen et al 2016) and to quantify flow field differences between simulations and experiments (Ameen et al 2017;Van Dam et al 2017). Similarly to the MSI, the local magnitude index (LMI), defined using magnitude subtraction rather than vector subtraction, has recently been used to compare LES simulations to PIV measurements across five planes within an optical engine (Zhao et al 2019).…”