• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.31-34
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• 2012

Numerical simulations of the steady and unsteady state were conducted for a coaxial swirl injector with Kerosene fuel. Non-premixed equilibrium model based on chemical equilibrium assumption was used as turbulence-chemistry interaction model. As an equations of state, SRK(Soave-Redlich-Kwong) EOS was applied to deal with the behavior of real fluid in a high pressure condition. Through the steady and unsteady computations, mean values of steady and time-averaged unsteady state were compared on the temperature and OH mass fraction and it was shown that the flame structure of steady state was different to that of time-averaged unsteady state.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.481-488
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• 2009

GIS is used to isolate large power electrical equipment using SF6 gas. While GIS has simple structure, it has few break down, relatively high reliability. But it is hard to check up faults for reason of pressure. Faults of GIS should have a ripple effect on community and be hard to recovery. Consequently, GIS imports a preventive diagnostic system to find internal faults in advance. It is most important that reliability on the GIS preventive diagnostic system, because it estimates abnormality of system by analysis result of collected data. But, exist system which used central data management is low efficiency, and hard to guarantee timeliness and accuracy of data. To guarantee timeliness and accuracy, the GIS preventive diagnostic system needs accordingly to use a real-time middleware. So, in this paper, to improve reliability of the GIS preventive diagnostic system, we use a middleware based on TMO for guaranteeing timeliness of real-time distributed computing. And we propose an improved GIS preventive diagnostic system applying data acquisition, monitoring and control methods based on the TMO model. The presented system uses the Communication Control Unit(CCU) for distributed data handling which is supported by TMO. CCU can improve performance of the GIS preventive diagnostic system by guaranteeing timeliness of data handling process and increasing reliability of data through the TMO middleware. And, it has designed to take full charge of overload on a data acquisition task had been processed in an exist server. So, it could reduce overload of the server and apply distribution environment from now. Therefore, the proposed system can improve performance and reliability of the GIS preventive diagnostic system and contribute to stable operation of GIS.

• Journal of The Korean Astronomical Society
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• v.37 no.4
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• pp.151-157
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• 2004

It is investigated quantitative relations between the magnetic storm magnitude and the solar wind parameters such as the Interplanetary Magnetic Field (hereinafter, IMF) magnitude (B), the southward component of IMF (Bz), and the dynamic pressure during the main phase of the magnetic storm with focus on the role of the interplanetary shock (hereinafter, IPS) in order to build the space weather fore-casting model in the future capable to predict the occurrence of the magnetic storm and its magnitude quantitatively. Total 113 moderate and intense magnetic storms and 189 forward IPSs are selected for four years from 1998 to 2001. The results agree with the general consensus that solar wind parameter, especially, Bz component in the shocked gas region plays the most important role in generating storms (Tsurutani and Gonzales, 1997). However, we found that the correlations between the solar wind parameters and the magnetic storm magnitude are higher in case the storm happens after the IPS passing than in case the storm occurs without any IPS influence. The correlation coefficients of B and $BZ_(min)$ are specially over 0.8 while the magnetic storms are driven by IPSs. Even though recently a Dst prediction model based on the real time solar wind data (Temerin and Li, 2002) is made, our correlation test results would be supplementary in estimating the prediction error of such kind of model and in improving the model by using the different fitting parameters in cases associated with IPS or not associated with IPS rather than single fitting parameter in the current model.

• Journal of the Korean Institute of Gas
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• v.19 no.4
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• pp.29-34
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• 2015

Accidents in laboratory dealing with chemicals have constantly occurred. In the case of a gas explosion or an accident related to leakage of chemical materials, the damage is much greater, thereby leading to a serious accident. Especially, the safety of laboratory in University is important because students build up knowledge and skills and accumulate experience as the main researchers. In this paper, 5 gases(CO, $NH_3$, $H_2$, $CH_4$, $N_2$) are selected to model since they are often used in university laboratories. From the scenarios where the gases are released, the diffusion process is estimated and analyzed to predict damage degree by PHAST v.6.7. Internal diffusion process is modeled through FLUENT which is Computational Fluid Dynamics(CFD) tool. Also, we compare indoor damage with outdoor one when discharged to the outside through the laboratory's window. In the modeling results, the outdoor damages for accident scenarios in the results are far less than then of real plants since the vessel usually used in laboratory(i.e. the capacity of the cylinder; 47 L or less) is significantly less than workplace's one(using ton measure). However as shown in the results small amount can have high consequences for indoor accidents.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.97-105
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• 2015

This paper is to analyze the efficiency of power consumption in logistic systems that are based on self-driving roller conveyors by the simulation technology. The improvement of the efficiency brings advantages for reducing greenhouse gas emission and logistics costs. A self-driving roller conveyor is operated only when products are loaded on itself. Thus, the self-driving roller conveyor systems consume less electric power than continuous-driving roller conveyor systems. In this paper, we design a DEVS (Discrete-Event based System) based simulation model and construct self-driving roller and continuous-driving roller conveyor models. For the verification and validation of the designed simulation system and conveyor models, we model a corresponding logistic model for the experimental environment and compare between the model and a real system. The main objective of this paper is to describe the power consumption advantage of self-driving roller conveyor based logistic systems using a simulation method.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.45-57
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• 2002

In this paper, the results gained by applying many impingement models to the cylinder and flat plate were analyzed in comparison with the experimental data to study a spray/wall interaction phenomena. To begin with, the behavior of spray injected normal to the wall was analysed using three different impingement models ; Naber and Reitz model(NR model), Watkins and Wang model(WW model) and Park and Watkins model(PW model) in the present calculation. The results obtained from these models were compared with experimental data of Katsura et. al. The results indicated that PW model was in better agreement with experimental data than the NR and WW model. Also f3r spray injected at 30DEG , the result of three models were compared with experimental data of Fujimoto et. al. The results showed that m model overpredicted the penetration in the radial direction because this model was based on the inviscid jet analogy. WW model did not predicted the radius and height of the wall spray effectively. It might be thought that this discrepancy was due to the lack of consideration of spray film velocity occurred at impingement site. The result of PW model agrees with the experimental data as time goes on. In particular, a height of the spray droplets was predicted more closely to the experimental data than the other two models. The results of PW model in which the spray droplets were distributed densely around the edge of droplet distribution shaped in a circle had an agreement with the experimental data of Fujimoto et. al. Therefore, it was concluded that PW model performed better than M and WW model for prediction of spray behavior. The numerical calculation using PW model performed to the cylinder similar to the real shape of DI engine. The results showed that vortex strength near the wall in the cylinder was stronger than that in the case of flat plate. Contrary to the flat plat, an existence of the side wall in the cylinder caused the tangential velocity component to be reduced and the normal velocity component to be increased. The flow tends to rotate to the inside of cylinder going upward to the right side wall of cylinder gradually as time passes. Also, the results showed that as the spray angle increases, the gas velocity distribution and the tumble flow seemed to be formed widely.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.136-143
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• 2018

Cellular automata have been applied to simulations in many fields such as astrophysics, social phenomena, fire spread, and evacuation. Using cellular automata, this study develops a model for consequence analysis of the dispersion of hazardous chemicals, which is required for risk assessments of and emergency responses for frequent chemical accidents. Unlike in cases of detailed plant safety design, real-time accident responses require fast and iterative calculations to reduce the uncertainty of the distribution of damage within the affected area. EPA ALOHA and KORA of National Institute of Chemical Safety have been popular choices for these analyses. However, this study proposes an initiative to supplement the model and code continuously and is different in its development of free software, specialized for small and medium enterprises. Compared to the full-scale computational fluid dynamics (CFD), which requires large amounts of computation time, the relative accuracy loss is compromised, and the convenience of the general user is improved. Using Python open-source libraries as well as meteorological information linkage, it is made possible to expand and update the functions continuously. Users can easily obtain the results by simply inputting the layout of the plant and the materials used. Accuracy is verified against full-scale CFD simulations, and it will be distributed as open source software, supporting GPU-accelerated computing for fast computation.

• Journal of Welding and Joining
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• v.32 no.5
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• pp.32-43
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• 2014

Welding and joining technology has become a core field. Therefore it is more widely applied to nonferrous metals, inorganic and polymeric materials. That is because the high performance, high function and diversification trend of materials used as industrial technology develops. In the laser welding process, STS 304 and SCP1-S were used as the base materials, the output density was fixed $7MW/cm^2$, the protective gas was argon(Ar) and the transfer rate was fixed 5 mm/sec. and it was progressed while the magnetic field is gradually increasing by 100 mT ranging 0 to 400 mT. The tensile test showed in average about 6 % tensile strength improvement in the case of the laser welding process using the magnetic fields. In the shielded metal arc welding process using SPHC only or the combination of SPHC+STS304 as base materials. The electric current was set at 80 Amperes and the protective gas used argon(Ar) the same as the laser welding process and the strength of magnetic fields. In the shielded metal arc welding process using the magnetic fields, the tensile tests showed about 5 % tensile strength improvement in the case of using SPHC only, 3 % tensile strength improvement in the case of using the combination of SPHC+ STS304. In comparing the results of numerical analysis to the results of experimental tests, it was revealed that the temperature, thermal stress distribution and the behavior of molten pool were similar to those of real tests. Consequently, it may be considered that the numerical assumption and the analytical model used in this study were reasonable.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.5
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• pp.51-59
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• 2008

DLN-2.6 combustion tuning was carried out for the maintenance of GE 7FA+e gas turbine at Seo-Incheon combined cycle power plant. DLN-2.6 combustion system has the higher level of yellow plume and combustion vibration problem in the initial operating mode than that of the base mode($100{\sim}160MW$). The objectives of this study are to investigate the causes of yellow plume and combustion vibration problems at the starting mode and to suggest the best operating condition for the reliable working of the real combustors. By the analysis of tuning data, we could conclude that a yellow plume is caused by the rich mixture(${\phi}{\sim}1$) in a PM 1 nozzle at mode 3($20{\sim}30MW$). In addition, the combustion vibration($120{\sim}140Hz$) might be related to the cold flow characteristics of PM 3 nozzles at mode 6B($40{\sim}45MW$).