Analysis of cyclic variations of liquid fuel–air mixing processes in a realistic DISI IC-engine using Large Eddy Simulation

2010 ◽  
Vol 31 (5) ◽  
pp. 845-849 ◽  
Author(s):  
D. Goryntsev ◽  
A. Sadiki ◽  
M. Klein ◽  
J. Janicka
Author(s):  
Ying Huai ◽  
Amsini Sadiki

In this work, Large Eddy Simulation (LES) has been carried out to analyze the turbulent mixing processes in an impinging jet configuration. To characterize and quantify turbulent mixing processes, in terms of scalar structures and degree of mixing, three parameters have been basically introduced. They are “mixedness parameter”, which represents the probability of mixed fluids in computational domain, the Spatial Mixing Deficiency (SMD) and the Temporal Mixing Deficiency (TMD) parameters for characterizing the mixing at different scalar scale degrees. With help of these parameters, a general mixing optimization procedure has then been suggested and achieved in an impinging jet configuration. An optimal jet angle was estimated and the overall mixing degree with this jet angle reached around six times more than the original design. It turns out that the proposed idea and methodology can be helpful for practical engineering design processes.


2004 ◽  
Author(s):  
L. Thobois ◽  
G. Rymer ◽  
T. Soulères ◽  
T. Poinsot

Author(s):  
Subin Thomas ◽  
Prasanth Prabhakaran ◽  
Will Cantrell ◽  
Raymond A. Shaw

AbstractWater vapor supersaturation in the atmosphere is produced in a variety of ways, including the lifting of a parcel or via isobaric mixing of parcels. However, irrespective of the mechanism of production, the water vapor supersaturation in the atmosphere has typically been modeled as a Gaussian distribution. In the current theoretical and numerical study, the nature of supersaturation produced by mixing processes is explored. The results from large eddy simulation and a Gaussian mixing model reveal the distribution of supersaturations produced by mixing to be negatively skewed. Further, the causes of skewness are explored using large eddy simulations (LES) and the Gaussian mixing model (GMM). The correlation in forcing of temperature and water vapor fields is recognized as playing a key role.


Author(s):  
P. Schiffmann ◽  
S. Gupta ◽  
D. Reuss ◽  
V. Sick ◽  
X. Yang ◽  
...  

2017 ◽  
Vol 99 (2) ◽  
pp. 353-383 ◽  
Author(s):  
Chao He ◽  
Wibke Leudesdorff ◽  
Francesca di Mare ◽  
Amsini Sadiki ◽  
Johannes Janicka

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