Validation of in-cylinder flow structure of controlled auto-ignition engine

2013 ◽  
Vol 10 (4) ◽  
pp. 305-312
Author(s):  
J. Beauquel ◽  
S. Ibrahim ◽  
R. Chen
Keyword(s):  
Experimental Data ◽  
Flow Structure ◽  
Transient Flow ◽  
Laser Doppler Anemometry ◽  
Auto Ignition ◽  
Geometry Configuration ◽  
Turbulent Flow Structure ◽  
Air Intake ◽  
Exhaust Valves ◽  
Actual Geometry

Numerical calculations have been carried out to investigate the in-cylinder transient flow structure of a controlled auto-ignition (CAI) engine running at speeds of 1,500rpm and 2,000rpm. The calculated turbulent flow structure and velocities are validated against published laser doppler anemometry (LDA) experimental data. The experimental data were re-processed to represent the time dependent mean velocities for all measured points. The actual geometry configuration of the engine is imported into the computational fluid dynamics (CFD) code used in this study. The simulations take into account the movement of the inlet, exhaust valves and the piston. The CFD simulations replicate the experimental work where only air was inserted into a driven optical engine. Also, to simulate an engine in controlled auto-ignition (CAI) mode, the same valve timing that allows 36% internal exhaust gas recirculation (IEGR) was applied for the air intake. The calculated results are found to agree well with the LDA measurements with an overall agreement of 75.06% at 1,500 rpm and 73.42% at 2,000 rpm.

Validation of in-cylinder flow of a controlled auto-ignition engine

2014 ◽  
Vol 11 (4) ◽  
pp. 421-430
Author(s):  
J. Beauquel ◽  
S. Ibrahim ◽  
R. Chen
Keyword(s):  
Experimental Data ◽  
Flow Structure ◽  
Transient Flow ◽  
Laser Doppler Anemometry ◽  
Auto Ignition ◽  
Geometry Configuration ◽  
Turbulent Flow Structure ◽  
Air Intake ◽  
Exhaust Valves ◽  
Actual Geometry

Numerical calculations have been carried out to investigate the in-cylinder transient flow structure of a controlled auto-ignition (CAI) engine running at speeds of 1500 rpm and 2000 rpm. The calculated turbulent flow structure and velocities are validated against published laser doppler anemometry (LDA) experimental data (Pitcher et al., 2003). The experimental data was reprocessed to represent the time dependent mean velocities for all measured points. The actual geometry configuration of the engine is imported into the computational fluid dynamics (CFD) code used in this study. The simulations take into account the movement of the inlet, exhaust valves and the piston. The CFD simulations replicate the experimental work where only air was inserted into a driven optical engine. Also, to simulate an engine in controlled auto-ignition (CAI) mode, the same valve timing that allows 36% internal exhaust gas recirculation (IEGR) was applied for the air intake. The calculated results found to agree well with the LDA measurements with an overall agreement of 75.06% at 1500 rpm and 73.42% at 2000 rpm.

Calculations of in-cylinder flow of a controlled auto-ignition (CAI) engine

2014 ◽  
Vol 11 (1) ◽  
pp. 61-70 ◽  
Author(s):  
J. Beauquel ◽  
S. Ibrahim ◽  
R. Chen
Keyword(s):  
Engine Speed ◽  
Transient Flow ◽  
Laser Doppler Anemometry ◽  
Turbulent Dissipation ◽  
Auto Ignition ◽  
Geometry Configuration ◽  
Computational Fluid Dynamics Cfd ◽  
Cylinder Flow ◽  
Exhaust Valves ◽  
Fresh Charge

After validation of the numerical model against published laser doppler anemometry (LDA) experimental data (Pitcher et al., 2003), numerical calculations have been carried out to investigate the in-cylinder transient flow structure of a controlled auto-ignition (CAI) engine running at speeds of 1,500 rpm and 2,000 rpm. The geometry configuration of the engine is imported into the computational fluid dynamics (CFD) code used in this study. The simulations take into account the movement of the inlet, exhaust valves and the piston. To simulate an engine in controlled auto-ignition (CAI) mode, the same valve timing that allows 36% gas residuals was applied to the model. The evolution of the flow pattern inside the cylinder at the symmetrical cross section is described. Also, the turbulence intensity (TI), the turbulent kinetic energy (TKE) and turbulent dissipation rate (TDR) are described for a better understanding of the effect of engine speed on the turbulences generated. The effects of engine speed on fresh charge velocity are also revealed.

scholarly journals Turbulent flow structure at a 90-degree open channel confluence: Accounting for the distortion of the shear layer

2016 ◽  
Vol 12 ◽  
pp. 130-147 ◽  
Author(s):  
Saiyu Yuan ◽  
Hongwu Tang ◽  
Yang Xiao ◽  
Xuehan Qiu ◽  
Huiming Zhang ◽  
...  
Keyword(s):  
Turbulent Flow ◽  
Shear Layer ◽  
Flow Structure ◽  
Open Channel ◽  
Turbulent Flow Structure ◽  
Channel Confluence

Turbulent flow structure at a discordant river confluence: Asymmetric jet dynamics with implications for channel morphology

2017 ◽  
Vol 122 (6) ◽  
pp. 1278-1293 ◽  
Author(s):  
Alexander N. Sukhodolov ◽  
Julian Krick ◽  
Tatiana A. Sukhodolova ◽  
Zhengyang Cheng ◽  
Bruce L. Rhoads ◽  
...  
Keyword(s):  
Turbulent Flow ◽  
Flow Structure ◽  
Channel Morphology ◽  
River Confluence ◽  
Turbulent Flow Structure

Thermal Model of a Thinned-Die Cooling System

2003 ◽  
Author(s):  
N. Boiadjieva ◽  
P. Koev
Keyword(s):  
Experimental Data ◽  
Thermal Model ◽  
Cooling System ◽  
Input Power ◽  
The Other ◽  
System Parameters ◽  
Air Intake ◽  
Optical Probing ◽  
Cooling Air ◽  
Better Than

For through-silicon optical probing of microprocessors, the heat generated by devices with power over 100W must be dissipated [1]. To accommodate optical probing, a seemingly elaborate cooling system that controls the microprocessor temperature from 60 to 100° C for device power up to 150W was designed [2]. The system parameters to achieve the desired thermal debug environment were cooling air temperature and air flow. A mathematical model was developed to determine both device temperature and input power. The 3-D heat equation that governs the temperature distribution was simplified to a case of a 1-D rod with one end at the device center and the other at the cooling air intake. Thus the cooling system was reduced to an analytical expression. From experimental data, we computed all coefficients in the model, then ran extensive tests to verify—the accuracy was better than 10% over the entire temperature and power ranges.

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