• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1556-1571
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• 1993

Nitrogen oxides ($NO_x$) are air pollutants which are generated from the combustion of fossil fuels. Stage combustion is an effective method to reduce $NO_x$ emissions. The effects of $NO_x$ reduction by stage combustion in a pilot scale combustor(6.6kW) have been investigated using propane gas flames laden with NH$_{3}$ as Fuel-N. The results in this study are follows; (1) $NO_x$ emissions are dependent on the reducing environment of fuel-rich zone regardless of total air ratio. The maximum $NO_x$ reduction is at the stoichiometric ratio of 0.8 to 0.9 in the reducing zone. (2) $NO_x$ reduction is maximum when burnout air is injected at the point where the oxygen in reducing zone is almost consumed. (3) $NO_x$ reduction is dependent upon the temperature of reducing zone with best effect above 950.deg. C in the reducing zone. (4) The fuel stage combustion is more effective to reduce $NO_x$ formation in the wide range of stoichiometric ratio than two stage combustion. (5) The results of this study could be utilized mainly in a design strategy for low $NO_x$ emission from the combustion of high fuel-nitrogen in energy sources ratio than as an indication of the absolute levels of $NO_x$ which can be achieved by stage combustion techniques in large scale facilities.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.7
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• pp.759-765
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• 2012

This study investigates the effect of diesel combustion strategies on exhaust emissions and hydrocarbon species emissions for a 1.7 L common rail direct injection diesel engine at 1500 rpm and 3.9 bar BMEP. The first strategy is a method to adopt no EGR with a split injection composed of pilot and main injection (split injection). The second is to adopt a moderate EGR rate with main injection only (single-1). The third is to use a high level of EGR and main injection with rail pressure increase, $i.e.$ low-temperature diesel combustion (single-2). Split injection and single-1 showed a renowned phenomenon of a PM-NOx trade-off, whereas single-2 was observed of a PM-NOx trade-off to reduce PM and NOx simultaneously. HC speciation results show that the split injection produced the least amount of HC species, regardless of the carbon number bin, followed by single-1 and single-2. The ratios of methane, acetylene, and CO to THC increased as a combustion A/F ratio is richer due to reduced oxygen content in the vicinity of the combustion zone, thus enhancing pyrolysis.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.05a
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• pp.285-288
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• 2009

In order to understand spray characteristics with inflowing air from the compressor in the APU gas turbine combustor, we performed spray visualization test by using ND-Yag Laser sheet beam. The sector combustor which size is 1/6 of the real combustor was manufactured. Turbo blower is used as an air supplying device to simulate gas turbine air flow condition. In the case of 75 m/s combustor inlet air flow condition, spray angle way increased and dispersed widely than without airflow condition.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.350-353
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• 2007

In this study, the genetic algorithm has been used for the real-time defect diagnosis on the operation of the aircraft gas-turbine engine. The component elements of the gas-turbine engine for consideriation of the performance deterioration is consist of the compressor, the gas generation turbine and the power turbine, repectively. Compared to the on-design point on the sea-level condition, the learning data has been increased 200 times in case of the off-design conditions for the altitude, the flight mach number and the fuel consumption. Therefore, enormous learning time has been required for the satisfied convergence. The optimum division has been proposed to decrease learning time as well as to obtain high accuracy. As results, the RMS errors of the defect diagnosis using the genetic algorithm have been estimated under 5 %.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.571-576
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• 2002

There have been a lot of considerations dealing with improving the performance of neuro-fuzzy system. The studies on the neuro-fuzzy modeling have largely been devoted to two approaches. First is to improve performance index of system. The other is to reduce the structure size. In spite of its satisfactory result, it should be noted that these are difficult to extend to high dimensional input or to increase the membership functions. We propose a novel neuro-fuzzy system based on the efficient clustering method for initializing the parameters of the premise part. It is a very useful method that maintains a few number of rules and improves the performance. It combine the various algorithms to improve the performance. The Expectation-Maximization algorithm of Gaussian mixture model is an efficient estimation method for unknown parameter estimation of mirture model. The obtained parameters are used for fuzzy clustering method. The proposed method satisfies these two requirements using the Gaussian mixture model and neuro-fuzzy modeling. Experimental results indicate that the proposed method is capable of giving reliable performance.