• Journal of the Korean Institute of Gas
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• v.13 no.2
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• pp.7-13
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• 2009

In order to make the critical path analysis of gas pipeline located under rigid pipes for interference behavior, FE analysis is performed considering real buried conditions of a drain and a gas pipe according to intersection angle of two pipes. A drain pipe and gas pipe have cover depth respectively 1.0m and 3.39m and this study considers a interference angle in the range of $0{\sim}90^{\circ}$. In this paper, the critical path is analyzed from the result of Ring Deflection and bending stress according to intersection angle. In the event intersection angle of two pipes equal to the critical path of lower pipe. The analysis results show that the critical path of lower gas pipe according to interference behavior has relation to intersection angle of two pipes.

• Journal of the Korean Society of Propulsion Engineers
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• v.3 no.1
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• pp.24-33
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• 1999

For performance prediction and diagnostics of gas turbine engines, linear and non-linear gas path analysis are applied. In order to find optimal instrument parameters to detect the physical faults such as (outing, erosion and corrosion, non-linear gas path analysis is used. A typical industrial gas turbine engine, TB5000, is used to study the effect of physical faults on engine performance. Through comparison of RMS error between linear and non-linear gas path analysis, the optimal instrument parameters can be defined. As a result, it is found that the linear GPA has the level of error introduced by the assumption of the linear mode: can be of the same order of magnitude as the fault being soughtwhile the non-linear GPA can be solved the non-linear relationships between dependent and independent parameters using an iterative method such as the Newton-Raphson method with sufficient accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.51-57
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• 2004

An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.218-221
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• 2006

High reliability and minimization of operating cost are important problems for both engine-manufacturer and user in operation of gas-turbine engine, for which various performance diagnostics including a fault identification have been a major issue nowadays. Performance estimation in the off-design conditions, however, encounters problems of large errors and of poor convergence because of much required data to be evaluated. In this study, a diagnostics code of engine performance has been developed by using GPA(Gas Path Analysis). Quantitative performance deterioration of the turbo-shaft engine for SUAV has been estimated with altitude variation and is compared with that obtained by GSP code.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.3
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• pp.82-89
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• 2006

Recently operation and maintenance cost of gas turbine engines has been issued as a major parameter in terms of designing and manufacturing. Accordingly, the conception that the maintenance and repair of an engine has to be conducted in assembled condition has been spreaded out. However, it is possible only if the prediction of the engine performance is clearly identified. In this study, therefore, a diagnostic code of the engine performance has been developed by using GPA(Gas Path Analysis) and Fuzzy Logic which can analyze the engine performance and estimate the health parameters. The prediction of the quantitative performance deterioration of the established model of the turbo-shaft engine for SUAV has been achieved in a satisfied level compared to that obtained by GSP code.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.10a
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• pp.267-270
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• 2003

An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach. Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.

• Journal of the Korean Institute of Gas
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• v.17 no.6
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• pp.39-45
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• 2013

The gas generated from the fire which is continuous until material is completely burned. We can analyze usual gas using chromatography analysis but it can not be applicated to analyze for the gas from the fire because which gas is enormously generated. Besides, chromatography analysis has the disadvantage that it can not continuously analyze the sample's representativness, gas from the fire, Fourier transform infrared spectroscopy, FT-IR, has been utilized for effective combustion gas analysis method in small-scale combustion and on-line analysis has been attempted continuously. However, continuous sampling of 3.5l/min can not be representativness of sample if the gas caused by a massive fire and space. And the gas sampling is practically impossible in such a case. In this study, we attempted remote analysis while overcoming the disadvantages of the current gas analysis by using an Open-Path Infrared Analyzer without pre-treatment of the sampling. For the remote analysis, quantitative analysis method was established regarding each combustion toxic gases. And we measured the gases from the fire that occurs in the real case.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.247-253
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• 2015

The components of an aero-engine gas path cannot be monitored in a timely way due to a lack of real-time monitoring technologies. As an attempt to address this problem, we have conducted research on a condition monitoring technology based on the charging characteristics of particles in an aero-engine gas path, and emphatically analyze the formation of particles in an aero-engine gas path, the charging mechanism of carbon particles and the factors that influence the charge quantity and polarity. The verification experiments are performed on the simulated experiment platform and a turbo-shaft engine test bench. The results show the carbon particles' carry charge, and an obvious change in the total electrostatic charge level in the aero-engine gas path due to the increased carbon particles produced by burning or abnormal metal particles; the charge number is related to the size of particles, and the bigger carbon particles carry a negative charge and metal particles carry a positive charge; the change in engine power can lead to an obvious change in the level of electrostatic charge in the gas path, and the change in electrostatic charge results from the extra carbon particles formed in the rich-oil burning process. The research provides a reference for establishing the baseline of electrostatic charge while the engine runs on different power. The study also demonstrates the validity of the electrostatic monitoring technology and establishes a base for developing the application of electrostatic monitoring technology in aero-engines.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.42-49
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• 2022

An underground electric switch is a high-voltage switch used in distribution network systems for a reliable power supply. Many studies are being conducted to expand the switch to use an eco-friendly gas using dry air instead of SF6 gas to reduce greenhouse gas emissions. In this study, a flow analysis model was established to improve the performance of an eco-friendly gas switch. The results were compared and reviewed through experiments. For the optimal arc grid design applied to the switch, the flow characteristics based on the flow path configuration and the changes in arcing time for each configuration were compared. Flow analysis can predict the switch flow distribution, and a comparative review of the flow path configurations of various methods is possible.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1909-1915
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• 2004

The hermetic rotary compressor is one of the most important components of an air conditioning system since it has a great effect on both the performance and the noise and vibration of the system. Noise and vibration occurs due to gas pulsation during the compression process and to unbalanced dynamic force. In order to reduce noise and vibration, it is necessary to identify their sources and transmission path and effectively control them. Many approaches have been tried in order to identify the noise transmission path of a compressor. However, identification has proven to be difficult since the characteristics of compressor noise are complicated due to the interaction of the compressor parts and gas pulsation. In this study, the statistical energy analysis has been used to trace the energy flow in the compressor and to identify the transmission paths from the noise source to the exterior sound field.