Flow field assessment in a fired spray-guided spark-ignition direct-injection engine based on UV particle image velocimetry with sub crank angle resolution

2007 ◽  
Vol 31 (2) ◽  
pp. 3023-3031 ◽  
Author(s):  
Claudia Fajardo ◽  
Volker Sick
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Field ◽  
Particle Image ◽  
Direct Injection ◽  
Spark Ignition ◽  
Direct Injection Engine ◽  
Field Assessment ◽  
Image Velocimetry ◽  
Crank Angle

scholarly journals Analysis of the interaction of Spray G and in-cylinder flow in two optical engines for late gasoline direct injection

2019 ◽  
Vol 21 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Christopher Geschwindner ◽  
Patrick Kranz ◽  
Cooper Welch ◽  
Marius Schmidt ◽  
Benjamin Böhm ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Field ◽  
Particle Image ◽  
Direct Injection ◽  
Standard Condition ◽  
Air Entrainment ◽  
Geometrical Parameters ◽  
Image Velocimetry ◽  
Liquid Spray ◽  
Cylinder Flow

An investigation of the interaction between the in-cylinder flow and the spray topology in two spray-guided direct injection optical engines is reported. The bulk flow field in the combustion chamber is characterized using particle image velocimetry. Geometrical parameters such as the axial penetration and the spray angle of the liquid spray are measured using Mie scatter imaging and/or diffuse back-illumination. The measured parameters are compared with data from a constant volume chamber available in the literature. For a late injection strategy, the so-called ECN Spray G standard condition, the mean values of the spray penetration do not seem to be significantly perturbed by the in-cylinder flow motion until the plumes approach the piston surface. However, spray probability maps reveal that cycle-to-cycle fluctuations of the spatial distribution of the liquid spray are affected by the magnitude of the in-cylinder flow. Particle image velocimetry during injection shows that the flow field in the vicinity of the spray plumes is heavily influenced by air entrainment, and that an upward flow in-between spray plumes develops. Consistent with previous research that demonstrated the importance of the latter flow structure for the prevention of spray collapse, it is found that increased in-cylinder flow magnitudes due to increased intake valve lifts or engine speeds enhance the spray-shape stability. Compared with cases without injection, the influence of the spray on the in-cylinder flow field is still noticeable approximately 2.5 ms after the start of injection.

Time-Resolved Particle Image Velocimetry Measurements of Nonreacting Flow Field in a Swirl-Stabilized Combustor Without and With Porous Inserts for Acoustic Control

2014 ◽  
Vol 137 (4) ◽  
Author(s):  
Joseph Meadows ◽  
Ajay K. Agrawal
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Field ◽  
Particle Image ◽  
Direct Injection ◽  
Combustion Noise ◽  
Turbulent Structures ◽  
Time Resolved ◽  
Turbulence Structures ◽  
Image Velocimetry ◽  
Acoustic Instabilities

Combustion noise and thermo-acoustic instabilities are of primary importance in highly critical applications such as rocket propulsion systems, power generation, and jet propulsion engines. Mechanisms for combustion instabilities are extremely complex because they often involve interactions among several different physical phenomena such as unsteady flame propagation leading to unsteady flow field, acoustic wave propagation, natural and forced hydrodynamic instabilities, etc. In the past, we have utilized porous inert media (PIM) to mitigate combustion noise and thermo-acoustic instabilities in both lean premixed (LPM) and lean direct injection (LDI) combustion systems. While these studies demonstrated the efficacy of the PIM concept to mitigate noise and thermo-acoustic instabilities, the actual mechanisms involved have not been understood. The present study utilizes time-resolved particle image velocimetry (PIV) to measure the turbulent flow field in a nonreacting swirl-stabilized combustor without and with PIM. Although the flow field inside the annulus of the PIM cannot be observed, measurements immediately downstream of the PIM provide insight into the turbulent structures. Results are analyzed using the proper orthogonal decomposition (POD) method and show that the PIM alters the flow field in an advantageous manner by modifying the turbulence structures and eliminating the corner recirculation zones and precessing vortex core (PVC), which would ultimately affect the acoustic behavior in a favorable manner.

scholarly journals 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

2021 ◽  
pp. 146808742110012
Author(s):  
Li Shen ◽  
Christopher Willman ◽  
Richard Stone ◽  
Tom Lockyer ◽  
Rachel Magnanon ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Direct Injection ◽  
Spark Ignition ◽  
Navier Stokes ◽  
Experimental Measurements ◽  
Intake Process ◽  
Image Velocimetry ◽  
Rans Simulations ◽  
Cylinder Flow

Computational fluid dynamics (CFD) simulations of the in-cylinder flow field are widely used in the design of internal combustion engines (ICEs) and must be validated against experimental measurements to enable a robust predictive capability. Such validation is complicated by the presence of both large-scale cycle-to-cycle variations and small-scale turbulent fluctuations in experimental measurements of in-cylinder flow fields. Reynolds averaged Navier-Stokes (RANS) simulations provide overall flow structures with acceptable accuracy and affordable computational cost for widespread industrial applications. Due to the nature of averaging physical parameters in RANS, its validation against experimental results obtained by particle image velocimetry (PIV) requires consideration of how best to average or filter the measured turbulent flows. In this paper, PIV measurements on the cross-tumble plane were recorded every five crank angle degrees for [Formula: see text] cycles during the intake process of a motored, optically accessible spark ignition direct injection (SIDI) engine. Several methods including ensemble averaging, speed-based averaging and low-order proper orthogonal decomposition (POD) reconstruction were applied to remove the fluctuations from experimental PIV vector fields and thus enable comparison to RANS simulations. Quantitative comparison metrics were used to evaluate the performances of each method in representing the intake jet. Recommendations are made on how to provide a fair validation between measured data and simulation results in highly fluctuating flow fields such as the engine intake jet.

Endoscopic 2D particle image velocimetry (PIV) flow field measurements in IC engines

2002 ◽  
Vol 33 (6) ◽  
pp. 794-800 ◽  
Author(s):  
U. Dierksheide ◽  
P. Meyer ◽  
T. Hovestadt ◽  
W. Hentschel
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Field ◽  
Particle Image ◽  
Field Measurements ◽  
Image Velocimetry ◽  
Ic Engines

scholarly journals 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

2021 ◽  
pp. 146808742110131
Author(s):  
Xiaohang Fang ◽  
Li Shen ◽  
Christopher Willman ◽  
Rachel Magnanon ◽  
Giuseppe Virelli ◽  
...  
Keyword(s):  
Flow Field ◽  
Particle Image ◽  
Direct Injection ◽  
Linear Manifold ◽  
Main Flow ◽  
Navier Stokes ◽  
Reduction Techniques ◽  
Image Velocimetry ◽  
Manifold Reduction ◽  
Relevance Index

In this article, different manifold reduction techniques are implemented for the post-processing of Particle Image Velocimetry (PIV) images from a Spark Ignition Direct Injection (SIDI) engine. The methods are proposed to help make a more objective comparison between Reynolds-averaged Navier-Stokes (RANS) simulations and PIV experiments when Cycle-to-Cycle Variations (CCV) are present in the flow field. The two different methods used here are based on Singular Value Decomposition (SVD) principles where Proper Orthogonal Decomposition (POD) and Kernel Principal Component Analysis (KPCA) are used for representing linear and non-linear manifold reduction techniques. To the authors’ best knowledge, this is the first time a non-linear manifold reduction technique, such as KPCA, has ever been used in the study of in-cylinder flow fields. Both qualitative and quantitative studies are given to show the capability of each method in validating the simulation and incorporating CCV for each engine cycle. Traditional Relevance Index (RI) and two other previously developed novel indexes: the Weighted Relevance Index (WRI) and the Weighted Magnitude Index (WMI), are used for the quantitative study. The results indicate that both POD and KPCA show improvements in capturing the main flow field features compared to ensemble-averaged PIV experimental data and single cycle experimental flow fields while capturing CCV. Both methods present similar quantitative accuracy when using the three indexes. However, challenges were highlighted in the POD method for the selection of the number of POD modes needed for a representative reconstruction. When the flow field region presents a Gaussian distribution, the KPCA method is seen to provide a more objective numerical process as the reconstructed flow field will see convergence with an increasing number of modes due to its usage of Gaussian properties. No additional criterion is needed to determine how to reconstruct the main flow field feature. Using KPCA can, therefore, reduce the amount of analysis needed in the process of extracting the main flow field while incorporating CCV.

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