• 시스템엔지니어링워크숍
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• s.1
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• pp.73-75
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• 2003

• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.270-274
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• 2004

• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.211-214
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• 2004

• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.188-195
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• 2004

• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.149-152
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• 2004

• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.73-78
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• 2004

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.12
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• pp.1143-1150
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• 2007

The fuel transfer characteristics of the jet pump between fuel tanks, which is applied in the smart UAV fuel supply system, were experimentally investigated. The operating conditions of the jet pump were setup to meet the engine requirement according to mission profile, and the jet pump performance was evaluated at those conditions. The pressure ratio and the efficiency of the jet pump were measured with the variation of flow ratio. In addition, the area ratio was taken into the consideration to examine the effect on the jet pump performance. From the evaluation results, the jet pump met the fundamental requirement to transfer fuel with the flow ratio of 2.23. In the case of the jet pump that is focused on the fuel transfer quantity rather than its efficiency, the flow ratio would be adjusted through the variation of area ratio of the jet pump within the permitted limit of pressure ratio.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.213-217
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• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute). For teaming the NN, a BPN with one hidden, one input and one output layer was used. The input layer had seven neurons of variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer used 6 neurons of degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network teaming and test was constructed using a gas turbine performance simulation program. From application results for diagnostics of the PW206C turboshaft engine using the learned networks, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.1013-1021
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• 2007

Design and performance analysis of the jet pump to transfer fuel between tanks in the smart UAV fuel supply system were carried out through one dimensional flow analysis and the flow analysis using a commercial CFD code. From the analysis results, it was proved that the jet pump was designed with the flow ratio of 2.23 that is the fundamental requirement of the jet pump design. The comparison results showed that the primary nozzle pressure is higher in the CFD analysis than in one dimensional flow analysis, mainly due to the underestimated loss coefficient of the primary nozzles. Consequently, the loss coefficients of the jet pump components should be determined more precisely for the design of the jet pumps with high performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.10
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• pp.805-812
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• 2013

The operational flight program(OFP) which has the functions of I/O processing with avionics, flight control logic calculation, fault diagnosis and redundancy mode is embedded in the flight control computer of Smart UAV. The OFP was developed in the environment of PowerPC 755 processor and VxWorks 5.5 real-time operating system. The OFP consists of memory access module, device I/O signal processing module and flight control logic module, and each module was designed to hierarchical structure. Memory access and signal processing modules were verified from bench test, and flight control logic module was verified from hardware-in-the-loop simulation(HILS) test, ground integration test, tethered test and flight test. This paper describes development environment, software structure, verification and management method of the OFP.