Particle Image Velocimetry Measurements: Application to In-Cylinder Flow for a Two Stroke Engine

1993 ◽  
Author(s):  
P. Guibert ◽  
M. Murat ◽  
B. Hauet ◽  
P. Keribin
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Image Velocimetry ◽  
Cylinder Flow ◽  
Stroke Engine

Effect of Piston Shape on Scavenging in a Two-Stroke Engine - A CFD Analysis

2014 ◽  
Vol 592-594 ◽  
pp. 1515-1519 ◽  
Author(s):  
Vivek Agrawal ◽  
J.M. Mallikarjuna
Keyword(s):  
Particle Image Velocimetry ◽  
Velocity Vector ◽  
Particle Image ◽  
Flow Characteristics ◽  
Cfd Analysis ◽  
Commercial Code ◽  
Image Velocimetry ◽  
Experimental Values ◽  
Cylinder Flow ◽  
Stroke Engine

This study focuses on effect of piston shape on in-cylinder flows in a conventional loop scavenged two-stroke engine using CFD. Three piston-shapes viz., flat, flat with center-bowl and flat with center-dome are analyzed along with standard piston. The CFD solution has been obtained by using commercial code STAR-CD. First the CFD results are compared with those of experimental values obtained from particle image velocimetry (PIV). For comparison among various piston shapes, various parameters viz., velocity vector plots, tumble ratio (TR), turbulent kinetic energy (TKE) at various crank angles are used. Scavenging and trapping efficiencies are also calculated for each piston configuration. From the results, it is found that flat with center-bowl piston is the best in terms of in-cylinder flow characteristics. It gives higher TR and TKE with very little effect on efficiencies.

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.

Machine learning–based analysis of in-cylinder flow fields to predict combustion engine performance

2019 ◽  
Vol 22 (1) ◽  
pp. 257-272 ◽  
Author(s):  
Alexander Hanuschkin ◽  
Steffen Schober ◽  
Johannes Bode ◽  
Jürgen Schorr ◽  
Benjamin Böhm ◽  
...  
Keyword(s):  
Machine Learning ◽  
Particle Image Velocimetry ◽  
Particle Image ◽  
Flow Fields ◽  
Effective Pressure ◽  
Indicated Mean Effective Pressure ◽  
Image Velocimetry ◽  
Crank Angle ◽  
Flow Features ◽  
Cylinder Flow

Cycle-to-cycle variations in an optically accessible four-stroke direct injection spark-ignition gasoline engine are investigated using high-speed scanning particle image velocimetry and in-cylinder pressure measurements. Particle image velocimetry allows to measure in-cylinder flow fields at high spatial and temporal resolution. Binary classifiers are used to predict combustion cycles of high indicated mean effective pressure based on in-cylinder flow features and engineered tumble features obtained during the intake and the compression stroke. Basic in-cylinder flow features of the mid-cylinder plane are sufficient to predict combustion cycles of high indicated mean effective pressure as early as 180 degree crank angle before the top dead center at 0 degree crank angle. Engineered characteristic tumble features derived from the flow field are not superior to the basic flow features. The results are independent of the tested machine learning method (multilayer perceptron and boosted decision trees) and robust to hyper-parameter selection.

The Influence of a Late In-Cylinder Air Injection on In-Cylinder Flow Measured with Particle Image Velocimetry (PIV)

2001 ◽  
Author(s):  
Martin Ekenberg ◽  
Raymond Reinmann ◽  
Eric Olofsson ◽  
Bertrand Gillet ◽  
Bengt Johansson
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Air Injection ◽  
Image Velocimetry ◽  
Cylinder Flow
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