• The KSFM Journal of Fluid Machinery
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• v.17 no.6
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• pp.13-20
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• 2014

It is necessary to design a compressor with high pressure ratio that satisfies the IMO(international maritime organization) NOx emission regulation for the marine diesel engine. Impeller was designed using the modified slip factor with the flow coefficient. The main purpose of this study is to investigate the sensitivity of the compressor performance by the vaned diffuser geometries. The first vaned diffuser type was based on a NACA airfoil, the second was channel diffuser, and the third was conformally transformated configuration of a NACA65(4A10)06 airfoil. The sensitivity of the performance was calculated using a commercial CFD program for three different diffuser geometries. The channel diffuser showed the wide range of operation and higher pressure characteristics, comparing with the others. This is attributed to the flow stability at diffuser. Combined with this results with impeller design, the optimized compressor was designed and verified by the test results.

• Journal of the Korean Institute of Gas
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• v.15 no.4
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• pp.33-38
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• 2011

The introduction of alternative fuels is beneficial to overcome the fuel shortage and reduce engine exhaust emissions. LPG and CNG are relatively clean fuel and considered as most promising alternative automotive fuels worldwide because of its emission reduction potential and lower fuel price compared to gasoline. Now a day’s adaptation of dual fuel approach is the growing as common trend. The two fuels can be successfully implemented with existing gasoline engine with little modification. The present study was done to analyze the performance and emissions analysis of a multi cylinder spark ignition engine fuelled with the benefits of CNG and LPG aseffective alternate automotive fuels by simply using them in an unmodified petrol engine. The test results indicate, the energy content of CNG and LPG is the most limiting factor in acceptance for fuel economy and performance reasons. Thermal efficiency was high for CNG lowest for gasoline and LPG between the two. BSFC, CO and HC were low and NOx was high for CNG and low for gasoline, LPG lies between the two.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.5
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• pp.334-342
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• 2009

Trends in the automotive market require the application of new engine technologies, which allows for the use of different types of fuel. Since ethanol is a renewable source of energy and has lower $CO_2$ emissions than gasoline, ethanol produced from biomass is expected to be used more frequently as an alternative fuel. It is recognized that for spark ignition (SI) engines, ethanol has the advantages of high octane number and high combustion speed. Due to the disadvantages of ethanol, it may cause extra wear and corrosion of electric fuel pumps. On-board hydrogen production out of ethanol is an alternative plan. This paper investigates the influence of ethanol fuel on SI engine performance, thermal efficiency and emissions. The combustion characteristics with hydrogen-enriched gaseous fuel from ethanol are also examined. As a result, thermal efficiency increase compared to gasoline. Also, reductions in $CO_2$, NOx, and THC combustion products for ethanol vs. gasoline are described.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.1
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• pp.138-143
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• 2006

Modification of injector, oil ring tension reduction and oil pump rotor re-matching with optimization of relevant engine control parameters could drive fuel consumption reduction of HSDI diesel engine. A 5 holes injector was replaced with a 6 holes with smaller nozzle hole diameter and 1.5 k factor, and evaluated in a view of fuel economy and emission trade-offs. With introducing smaller nozzle hole diameter injector, PM(Particulate Matter) was drastically decreased for low engine load and low engine rpm. Modification of oil pump and oil ring was to reduce mechanical friction and be proved to better fuel economy. Optimization of engine operating conditions was a great help for the low fuel consumption. Influence of the engine operating parameters· including pilot quantity, pilot interval, air mass and main injection timing on fuel economy, smoke and NOx has been evaluated with 14 points extracted from NEDC(New European Driving Cycle) cycle. The fuel consumption was proved to $7\%$ improvement on an engine bench and $3.7\%$ with a vehicle.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.604-613
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• 2006

The chemical composition of $PM_{2.5}$ such as ${SO_4}^{2-},\;{NO_3}^-,\;Cl^-,\;{NH_4}^+,\;Ca^{2+},\;K^+,\;Na^+,\;Mg^{2+}$, OC, and EC and the concentrations of reactive trace gases including $O_3,\;CO,\;NOx,\;SO_2,\;and\;H_2O_2$ were measured at Gosan in Jeju Island during March $13{\sim}30$, as a part of the Atmospheric Brown Clouds-East Asian Regional Experiment 2005(ABC-EAREX2005). The average mass concentrations of $PM_{2.5}$ was 27.3 ${\mu}g/m^3$, of which OC showed the highest concentration as 4.22 ${\mu}g/m^3$ and nss ${SO_4}^{2-}$ was the second highest as 3.34 ${\mu}g/m^3$. During that period, average concentrations of CO and $O_3$ was about 300 ppbv and 56 ppbv, respectively. For the whole experiment, the correlations of CO with ${SO_4}^{2-}$ and EC were very good, which suggests that CO can be used as tracer for the formation of fine aerosols. Several pollution and dust episodes were identified by the enhancement of CO, OC, EC, nss ${SO_4}^{2-},\;or\;Ca^{2+}$ concentrations or their ratios. In conjunction with factor analysis, air trajectory analysis, and comparison with emission inventories, these results indicate the spring aerosols collected at Gosan was strongly influenced by Asian outflows.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.221-228
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• 2013

An experimental study was carried out to investigate the effects of the injection timing on the spray and combustion characteristics in a spray-guided direct-injection spark-ignition (DISI) engine under lean stratified operation. An in-cylinder pressure analysis, exhaust emissions measurement, and visualization of the spray and combustion were employed in this study. The combustion in a stratified DISI engine was found to have both lean premixed and diffusion controlled flame combustion characteristics. The injection timing condition corresponding to the stratified mixture characteristics was verified to be a dominant factor for these flame characteristics. For the early injection timing, a non-luminous blue flame and low combustion efficiency were observed as a result of the lean homogeneous mixture formation. On the other hand, a luminous sooting flame was shown at the late injection timing because of an under-mixed mixture formation. In addition, the smoke emission and incomplete combustion products were increased at the late injection timing as a result of the increased locally rich area. On the other hand, the NOx emissions decreased and IMEP increased as the injection timing retarded. The combustion phasing produced by the injection timing was verified as the reason for this observation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.40-49
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• 2004

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN), discuss a comprehensive design methodology and carry out a series of numeric experiments. The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional SOPNN. In order to generate the structurally optimized SOPNN, GA-based design procedure at each stage (layer) of SOPNN leads to the selection of preferred nodes (or PNs) with optimal parameters- such as the number of input variables, input variables, and the order of the polynomial-available within SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. A detailed design procedure is discussed in detail. To evaluate the performance of the GA-based SOPNN, the model is experimented with using two time series data (gas furnace and NOx emission process data of gas turbine power plant). A comparative analysis shows that the proposed GA-based SOPNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.105-105
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• 2011

ZnO is a promising material since it could be applied to many fields such as solar cells, laser diodes, thin films transistors and gas sensors. ZnO has a wide and direct band gap for about 3.37 eV at room temperature and a high exciton binding energy of 60 meV. In particular, ZnO features high sensitivity to toxic and combustible gas such as CO, NOX, so on. The development of gas sensors to monitor the toxic and combustible gases is imperative due to the concerns for enviromental pollution and the safety requirements for the industry. In this study, we investigated the effect of substrate temperature and post-annealing on structural and electrical properties of ZnO thin films. ZnO thin films were deposited by pulsed laser deposition (PLD) at various temperatures at from room temperature to $600^{\circ}C$. After that, post-annealing were performed at $600^{\circ}C$. To inspect the structural properties of the deposited ZnO thin films, X-ray diffraction (XRD) was carried out. For gas sensors, the morphology of the films is dominant factor since it is deeply related with the film surface area. Therefore, the atomic force microscopy (AFM) and field emission scanning electron microscopy (FE-SEM) were used to observe the surface of the ZnO thin films. Furthermore, we analyzed the electrical properties by using a Hall measurement system.