• Journal of ILASS-Korea
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• v.18 no.1
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• pp.61-65
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• 2013

In case of GDI engine, shape of injected fuel and injection mass are one of the most important factors for good fuel efficiency and power. But it should be too inefficient and difficult to acquire injection mass data by experiment because condition in engine vary with temperature, pressure, and so on. So, this paper suggests the AMESim (Advanced Modeling Environment for Simulation of Engineering Systems) as simulation program to calculate injection mass. For both simulation and experiment, n-heptane is used as fuel. In AMESim, I modeled the GDI injector and simulated several cases. In experiment, I acquired the injection mass using Bosch method to apply ambient pressure. The AMESim show reasonable result in comparison with experimental data especially at injection pressure 15 MPa. Other conditions are also in good accord with experimental data but error is a little bit large because the injection mass is so low.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.5
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• pp.397-405
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• 2003

Heat and fluid flow in a compressor into which liquid refrigerant is injected for the purpose of reducing discharge gas temperature in a heat pump system has been numerically studied. A mechanistic approach encompassing liquid jet breakup and droplet evaporation has been performed to investigate the effects of liquid injection on the spacial and temporal variation of the gas temperature and pressure inside the compressor cylinder. Various parameters, such as liquid injection mass, time, duration and droplet size, are considered in the present study to elucidate the flow field inside the compressor. As the injection mass is increased, discharge gas temperature is decreased, while the pressure is increased due to the added mass of the injection. For the injected liquid mass corresponding to 15% of the total vapor mass in the cylinder, the discharge gas temperature drops by 22.4 K. It is observed that the droplet size plays a major role in the evaporation rate of the droplets that determines the degree of the discharge temperature drop.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.293-296
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• 2007

Using the T3 free-piston shock tunnel in ANU, the cavity frequency and flow characteristics of no mass-injection, inclined mass-injection before the cavity, parallel or reverse mass-injection in the cavity are investigated in the case of Mach 3.7 inflow condition. No mass-injection doesn't have the harmonic frequencies but has high amplitude of pressure spectrum at 10 kHz. Inclined mass-injection attenuates the cavity flow fluctuation as disturbing the shear layer reflection at the trailing edge. Parallel mass-injection flow reflects at the trailing edge of the cavity directly hence, increases the cavity flow fluctuation at high injection pressure.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.63-74
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• 2001

In this study, a cycle simulation program of a Unit-Injection(UI) system was developed to estimate the injection performance of newly designed injection system. A fundamental theory of the simulation program is based on the conservation law of mass. Loss of fuel mass in the system due to leakage, compressibility effect of the liquid fuel and friction loss in the control volume was considered in the algorithm f the program. For the evaluation of the simulation program developed, the experimental result which was offered by the Technical Research Center of Doowon Precision Industry Co. was incorporated. Two main parameters; the maximum pressure in the plunger chamber and total fuel mass(kg) injected into the engine cylinder per cycle, were measured and compared with the simulation results. It was found that the maximum error rate of the simulation result to the experimental output was less than 3% in the rated rotational speed (rpm) range of the plunger cam.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Design & Manufacturing
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• v.14 no.3
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• pp.1-7
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• 2020

This paper predicts the mass and the length of injection-molded products through the Artificial Neural Network (ANN) method. The ANN was implemented with 5 input parameters and 2 output parameters(mass, length). The input parameters, such as injection time, melt temperature, mold temperature, packing pressure and packing time were selected. 44 experiments that are based on the mixed sampling method were performed to generate training data for the ANN model. The generated training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. A random search method was used to find the optimized hyper-parameter of the ANN model. After the ANN completed the training, the ANN model predicted the mass and the length of the injection-molded product. According to the result, average error of the ANN for mass was 0.3 %. In the case of length, the average deviation of ANN was 0.043 mm.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.2
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• pp.80-86
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• 1997

This experiment was undertaken to investigate spray characteristics of the conventional injection system and the ultrasonic energy added injection system. Sauter mean diameter was measured under the variation of injection pressure and the spray distance. To measure the droplet size, we used the Malvern system 2600C. The spray angle and mass distribution were analyzed to the CCD camera and the patternater. After experiment, it was found that the ultrasonic energy added injection system had smaller Sauter mean diameter of droplet, wider mass distribution and wider spray angle than the conventional injection system had.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.233-242
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• 2023

In this paper, the effect of mass injection on the control of tip vortex cavitation was studied experimentally. A mass injection system for a 3D hydrofoil was designed to control the location of injection as well as the injection rate. A series of cavitation tests were carried out in a cavitation tunnel for different injection locations and rates. The cavitation behaviour was observed using a high-speed camera and the corresponding noise was measured using a hydrophone installed in the observation window. The results showed that the tip vortex cavitation was suppressed under certain conditions and the noise was reduced in some frequency bands. It was also found that there is a location where the effect of mass injection could be maximized and hence the noise reduction.

• Aerospace Engineering and Technology
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• v.10 no.1
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• pp.129-135
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• 2011

A study of efficient plume cooling by core water injection type was performed by computational fluid dynamics. A side injection type is well known, on the contrary, a core injection type is not well known. In order to figure out the characteristics of core injection type, several calculations were performed by computational fluid dynamics along various mass flow rates and locations of water injection. On the basis of analysis it was the adequate cooling condition that water mass flow rate to total mass flow rate was two times at least and location of water injections was L/De=1.2.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.645-652
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• 1994

The leading edge of a turbine blade was simulated as a circular cylindrical surface. The effect of free-stream turbulence on the mass transfer upstream of the injectionhole has been investigated experimentally. The effects of injection location, blowing ratio on the Sherwood number distribution were examined as well. The mass transfer coefficients were measured by a naphthalene sublimation technique. The free-stream Reynolds number based on the cylinder diameter is 53,000. Other conditions investigated are: free-stream turbulence intensities of 3.9% and 8.0%, injection locations of $40^{\circ}$, $50^{\circ}$, and $60^{\circ}$ from the front stagnation point of the cylinder, and blowing ratios of 0.5 and 1.0. The role of the horseshoe vortex formed upstream edge of the injected jet is dicussed in detail. When the blowing ratio is unity, and the coolant jet is injected at $40^{\circ}$, the mass transfer upstream of the jet is not affected by the coolant jet at all. On the other hand, when the injection hole is located beyond $50^{\circ}$, the mass transfer upstream edge of the injection hole suddenly increases due to the formation of the horseshoe vortex, but it dereases as the free-stream turbulence intensity increases because the strength of the horseshoe vortex structure becomes weakened. The role of the horseshoe vortex is clearly evidenced by placing a rigid rod at the injection hole instead of issuing the jet. In the case of the rigid rod, the spanwise Sherwood number upstream of the injection hole is much larger due to the intense influence of the horseshoe vortex.