Model Calibration for Spray Penetration and Mixture Formation in a High Pressure Fuel Spray Using a Micro-Genetic Algorithm and Optical Data

2005 ◽  
Author(s):  
J. Weber ◽  
P. Spiekermann ◽  
N. Peters
Keyword(s):  
Genetic Algorithm ◽  
High Pressure ◽  
Model Calibration ◽  
Optical Data ◽  
Fuel Spray ◽  
Mixture Formation ◽  
Spray Penetration ◽  
Micro Genetic Algorithm

Fuel Spray Penetration in High Pressure Diesel Engines

2007 ◽  
Author(s):  
W. A. Abdelghaffar ◽  
K. Karimi ◽  
M. R. Heikal
Keyword(s):  
High Pressure ◽  
Diesel Engines ◽  
Fuel Spray ◽  
Spray Penetration

Spray Visualization of Biodiesel and Diesel in a High Pressure Chamber

2014 ◽  
Vol 931-932 ◽  
pp. 1043-1047 ◽  
Author(s):  
Prathan Srichai ◽  
Chinda Chareonphonphanich ◽  
Preechar Karin ◽  
Nuwong Chollacoop
Keyword(s):  
High Pressure ◽  
High Speed ◽  
Initial Conditions ◽  
Video Camera ◽  
Pressure Chamber ◽  
Spray Angle ◽  
Biodiesel Fuel ◽  
High Pressure Chamber ◽  
Mixture Formation ◽  
Spray Penetration

The present research attempted to characterize fuel spray pattern, such as spray angle, spray penetration and their mixture formation by recourse to images analysis. Diesel and biodiesel were used to investigate via a single hole injector (solinoild type) in a constant volume high-pressure chamber. In this experimental study, the spray characteristics of diesel and biodiesel fuel were comparatively evaluated. Initial conditions were ambient temperature, ambient density of 21 kg/m3, injection durations varied from 0.5 and 1 ms and rail pressure of 400 and 800 bar. The series of images were captured by high speed video camera with resolution of 7,500 frames per second and shutter speed of 1/10,000 sec under Schlieren photography technique. The result showed the biodiesel spray penetration was longer than that of the diesel, and spray angle of biodiesel in start injection was larger than biodiesel. From the results, it can be concluded that the higher the density and viscosity of biodiesel, the stronger the effect on the spray mixture formation.

The Role of Porous Media in Homogenization of High Pressure Diesel Fuel Spray Combustion

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Navid Shahangian ◽  
Damon Honnery ◽  
Jamil Ghojel
Keyword(s):  
High Pressure ◽  
Porous Media ◽  
High Speed ◽  
Fuel Spray ◽  
Compression Ignition Engines ◽  
System Pressure ◽  
Novel Approach ◽  
Air Mixing ◽  
The Media

Interest is growing in the benefits of homogeneous charge compression ignition engines. In this paper, we investigate a novel approach to the development of a homogenous charge-like environment through the use of porous media. The primary purpose of the media is to enhance the spread as well as the evaporation process of the high pressure fuel spray to achieve charge homogenization. In this paper, we show through high speed visualizations of both cold and hot spray events, how porous media interactions can give rise to greater fuel air mixing and what role system pressure and temperature plays in further enhancing this process.

Fuel Spray Trajectory in Diesel Engines

1978 ◽  
Vol 100 (2) ◽  
pp. 326-332 ◽  
Author(s):  
M. M. Elkotb ◽  
N. M. Rafat
Keyword(s):  
Heat Transfer ◽  
Theoretical Model ◽  
Working Conditions ◽  
Fuel Spray ◽  
Air Velocity ◽  
Spray Penetration ◽  
Injection Angle ◽  
Velocity Pattern ◽  
Spray Volume ◽  
Spray Velocity

A detailed investigation of the effect of the shape of an open combustion chamber for diesel engine on the air velocity pattern, and consequently, on the trajectory of the fuel spray is given in this paper. A theoretical model for the calculation of the spray penetration, taking into consideration the heat transfer to the droplet, the variation of the drag force with Reynolds number, and air velocity pattern, is suggested. The effect of some working conditions on the spray shape, trajectory, and penetration is experimentally studied to verify the theoretical model and to correlate the results of using different medium pressures, initial spray velocity, and injection angle on the magnitude of fuel spray diameter and spray volume.

Development of stochastically perturbed parameterization scheme for the Noah Land Surface Model with the optimized random forcing parameters using the micro-genetic algorithm

2021 ◽  
Author(s):  
Sujeong Lim ◽  
Claudio Cassardo ◽  
Seon Ki Park
Keyword(s):  
Genetic Algorithm ◽  
Land Surface ◽  
Weather Forecasting ◽  
Land Surface Model ◽  
Surface Model ◽  
Ensemble Spread ◽  
Near Surface ◽  
Random Forcing ◽  
Micro Genetic Algorithm ◽  
Stochastically Perturbed

<p>The ensemble data assimilation system is beneficial to represent the initial uncertainties and flow-dependent background error covariance (BEC). In particular, the inevitable model uncertainties can be expressed by ensemble spread, that is the standard deviation of ensemble BEC. However, the ensemble spread generally suffers from under-estimated problems. To alleviate this problem, recent studies employed stochastic perturbation schemes to increases the ensemble spreads by adding the random forcing in the model tendencies (i.e., physical or dynamical tendencies) or parameterization schemes (i.e., PBL, convective scheme, etc.). In this study, we focus on the near-surface uncertainties which are affected by the interactions between the land and atmosphere process. The land surface model (LSM) provides various fluxes as the lower boundary condition to the atmosphere, influencing the accuracy of hourly-to-seasonal scale weather forecasting, but the surface uncertainties were not much addressed yet. In this study, we developed the stochastically perturbed parameterization (SPP) scheme for the Noah LSM. The Weather Research and Forecasting (WRF) ensemble system is used for regional weather forecasting over East Asia, especially over the Korean Peninsula. As a testbed experiment with the newly-developed Noah LSM-SPP system, we first perturbed the soil temperature — a crucial variable for the near-surface forecasts by affecting sensible heat fluxes, land surface skin temperature and surface air temperature, and hence lower-tropospheric temperature. Here, the random forcing used in perturbation is made by the tuning parameters for amplitude, length scale, and time scales: they are commonly determined empirically by trial and error. In order to find optimal tuning parameter values, we applied a global optimization algorithm — the micro-genetic algorithm (micro-GA) — to achieve the smallest root-mean-squared errors. Our results indicate that optimization of the random forcing parameters contributes to an increase in the ensemble spread and a decrease in the ensemble mean errors in the near-surface and lower-troposphere uncertainties. Further experiments will be conducted by including soil moisture in the testbed.</p>

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