• 한국분무공학회지
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• 제22권1호
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• pp.29-35
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• 2017

This paper describes the effects of spray breakup model constants on spray and combustion characteristics in single cylinder compression engine. KIVA-3V code coupled with a CHEMKIN chemistry solver was used for numerical analysis. In this study, spray simulations and combustion simulations are studied simultaneously. Spray simulation was conducted in constant volume to reduce the effects of air-flow as swirl or tumble. The model validation was conducted and there are little difference between experiments and simulation, this differences were reasonable. In spray simulation, the effects of model constants on spray tip penetration, spray patter and SMD were studied. Furthermore, the analysis of effects of breakup variables on combustion and emissions characteristics was conducted. The results show the KH-RT breakup model constants affects spray and combustion characteristics strongly. Increasing KH model variable (B1) and RT model constants ($C_{\tau}$, $C_{RT}$) induced slower breakup time.

• 한국자동차공학회논문집
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• 제5권1호
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• pp.87-100
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• 1997

The ability of turbulence model to accurately describe the complex characteristics of the flow field and the fuel spray is of great importance in the optimum design of diesel engine. The numerical simulations of the flow field and the spray characteristics within the combustion chamber of direct injection model entgine are performed to examine the applicability of turbulence model. The turbulence models used are the RNG $\varepsilon$ model and the modified $\varepsilon$ model which included the compressibility effect due to the compression/expansion of the charges. In this study, the predicted results in the quiescent condition of direct injection model engine show reasonable trends comparing with the experimental data of spray characteristics, i. e., spray tip penetration, spray tip velocity. The results of eddy viscosity obtained using the $\varepsilon$ model in the spray region is significantly larger than that obtained using the RNG $\varepsilon$ model. The application of the RNG model seems to have some potential for the simulations of the spray characteristics, e. g., spray tip penetration, spray tip velocity, droplets distribution over the $\varepsilon$ model.

• 한국분무공학회지
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• 제12권2호
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• pp.101-107
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• 2007

The purpose of this study is to analyze spray and evaporation characteristics of DME fuel at the high pressure and temperature. For the numerical analysis of dimethyl ether(DME) fuel spray characteristics, hybrid breakup model was applied to the DME spray and its breakup process. In order to obtain experimental results for comparison with the predicted ones, the visualization of the spray evolution process was executed by using a Nd:YAG laser. Also, the numerical investigation was conducted by the two hybrid models for primary and secondary breakup of the DME spray. The primary breakup model was used the Kelvin-Helmholtz(KH) breakup model. In the secondary breakup process, Rayleigh-Taylor(RT) and Drop Deformation Breakup(DDB) model was applied. The results of this study provide the macroscopic characteristics of the spray such as spray tip penetration and cone angle, and prediction accuracy of the two hybrid model.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집B
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• pp.919-924
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• 2000

Spray impingement model and fuel film formation model were developed and incorporated into the computational fluid dynamics code, STAR-CD. The spray/wall interaction process were modelled by considering the change of behaviour with surface temperature condition and fuel film formation. We divided behaviour of fuel droplets after impingement into stick, rebound and splash using Weber number and parameter K. Spray impingement model accounts for mass conservation, energy conservation and heat transfer to the impinging droplets. A fuel film formation model was developed by Integrating the continuity, the Navier-Stokes and the energy equations along the direction of fuel film thickness. The validation of the model was conducted using diesel spray experimental data and gasoline spray impingement experiment. In all cases, the prediction compared reasonably well with experimental results. Spray impingement model and fuel film formation model have been applied to a direct injection diesel engine combustion chamber.

• 한국분무공학회지
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• 제13권3호
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• pp.117-125
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• 2008

The correlations for the prediction of maximum liquid-phase penetration in diesel spray are reviewed in this study. The existing models developed for the prediction of maximum liquid-phase penetration can be categorized as the zero-dimensional (empirical) model, the multi-dimensional model and the other model. The existing zero-dimensional model can be classified into four groups and the existing multidimensional models can be classified into three groups. The other model includes holistic hydraulic and spray model. The maximum liquid-phase penetration is mainly affected by nozzle diameter, fuel volatility, injection pressure, ambient gas pressure, ambient gas density and fuel temperature. In the case of empirical correlations incorporated with spray angle, the predicted results will be different according to the selection of correlation for spray angle. The research for the effect of boiling point temperatures on maximum liquid-phase penetration is required. In the case of multidimensional model, there exist problems of the grid and spray sub-models dependency effects.

• Journal of Advanced Marine Engineering and Technology
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• 제26권2호
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• pp.181-191
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• 2002

Spray calculation has been studied to understand the behavior of the spray in a combustion chamber But the spray dispersion has not been predicted properly in a high velocity injection spray or a wall impaction spray. In this study the extended grazing collision model is applied to improve the problem. The gas phase is modelled by the Eulerian continuum conservation equations of mass, momentum, energy and fuel vapour fraction. The liquid phase is modelled following the discrete droplet model approach in Lagrangian form. The droplet distributions, penetration, width and gas flows are compared for the cases with or without extended model. The extended collision model makes the results better.

• 한국분무공학회지
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• 제27권2호
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• pp.57-65
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• 2022

The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R² and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.

• 한국분무공학회지
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• 제28권1호
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• pp.1-9
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• 2023

In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R² and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.3467-3472
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• 2007

The effects of the wall geometry on the spray-wall impingement process of a hollow-cone fuel spray emerging from a high-pressure swirl injector of the Gasoline Direct Injection (GDI) engine were investigated by means of a numerical method. The ized Instability Sheet Atomization (LISA) & Aerodynamically Progressed Taylor Analogy Breakup (APTAB) model for spray atomization process and the Gosman model were applied to model the atomization and wall impingement process of the spray. The calculation results of spray characteristics, such as a spray development process and a radial distance after wall impingement, compared with the experimental ones by the Laser Induced Exciplex Fluorescence (LIEF) technique. It was found that the radial distance of the cavity angle of 90$^{circ]$ after wall impingement was the shortest and the ring shaped vortex was generated near the wall after spray-wall impingement process.

• 한국자동차공학회논문집
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• 제15권4호
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• pp.124-131
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• 2007

The numerical study on behavior of impinging spray from high-pressure swirl injector under various ambient temperatures was performed by using spray vaporization model and spray-wall impingement model implemented in modified KIVA code, and these spray models were estimated by comparison with experimental results. To compute the spray-wall impingement process, the Gosman model, which is based on the droplet behavior after impingement determined by experimental correlations, was used. The modified Abramzon and Sirignano model, that includes the effects of variable thermodynamic properties and non-unitary Lewis number in the gas film, was adapted for spray vaporization process. The exciplex fluorescence measurements were also conducted for comparison. The experimental and numerical analysis were carried out at the ambient pressures of 0.1 MPa and at the ambient temperature of 293 K and 473 K, and the spray characteristics, such as spray-wall impingement process, gas velocity field, SMD and vapor concentration, were acquired. It was found that the impinging spray develops active and SMD is small at vaporization conditions.