• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1184-1191
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• 2009

In order to reduce the download around the Smart UAV(SUAV) at Transition mode, flow control using synthetic jet has been performed. Many of the complex tilt rotor flow features are captured including the leading and trailing edge separation, and the large region of separated flow beneath the wing. Based on the results of part 1 of the present work, synthetic jet is located at 0.01c, $0.95c_{flap}$ and it is operated with the non-dimensional frequency of 0.5, 5 to control the leading edge and trailing edge separation. Consequently, download is substantially reduced compared to with no control case at transition mode using leading edge jet only. The present results show that the overall flight performance and stability of the SUAV can be remarkably improved by applying the active flow control strategy based on synthetic jet.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1173-1183
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• 2009

In order to reduce the download around the Smart UAV(SUAV) at hovering, flow control using synthetic jet has been performed. Many of the complex tilt rotor flow features are captured including the leading and trailing edge separation, and the large region of separated flow beneath the wing. In order to control the leading edge and trailing edge separation, synthetic jet is located at 0.01c, $0.3c_{flap}$, $0.95c_{flap}$. As non-dimensional frequency, the flow pattern is altered and the rate of drag reduction is changed. The results show that synthetic jets shorten the vortex period and decrease the vortex size by changing local flow structure. By using leading edge jet and trailing edge jet, download is efficiently reduced compared to no control case at hovering mode.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.2
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• pp.15-22
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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 is being developed by KARI (Korea Aerospace Research Institute). For teeming the NN(Neural Network), a BPN(Back Propagation Network) with one hidden, one input and one output layer was used. The input layer has seven neurons: variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer uses 6 neurons: degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine, respectively, Database for network teaming and test was constructed using a gas turbine performance simulation program. From application of the learned networks to diagnostics of the PW206C turboshaft engine, 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.43 no.10
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• pp.920-927
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• 2015

In this paper, numerical results of sectional analysis and stress recovery were compared with the results of VABS through the blade analysis library. The results of recovery analysis for one-dimensional model including the stiffness matrix is compared with the calculated three-dimensional stress results of three-dimensionial FEM based on the principle of virtual work. We discuss the configuration of the blade analysis library and compare verifications of numerical analysis results of VABS. Blade analysis library through dimensional reduction and stress recovery is intended to be utilized in conjunction with pre- and post-processing of the analysis program of the composite blade, high-altitude uav's wing, wind blades and tilt rotor blade.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.149-153
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle). In ordo to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.

• Journal of the Korean Society of Propulsion Engineers
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• v.9 no.4
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• pp.81-88
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle). In order to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. When the performance analysis is performed at far away operation conditions from the design point, in case of use of e component map by the traditional scaling method, the error of the performance analysis results is greatly increasing. In the other hand, if in case of use of the compressor map generated by the proposed GAs scheme, the performance analysis results are closely met with those by the performance deck, EEPP.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.889-891
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• 2017

Usually piston or rotary engines are installed at UAV's under 100 kg payload class. Those engine are less expensive and easy to get, but they require higher operating and maintenance costs due to shorter life and unique fuel usage. They are also too noisy to operate in urban area and have too strong vibration to carry sophisticated payloads. On the contrary, a gas turbine engine has drawbacks like higher specific fuel consumption and weight to power ratio, even it has many operating and maintenance benefits. This study aims to design a small turboshaft engine with a recuperator to overcome those demerits. A tilt rotor UAV(TR-60) developed by KARI was chosen as an imaginary target aircraft, and engine power and size were derived from it. This paper describes engine requirements, design process, and initial reference point cycle design.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.46-52
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• 2004

A design methodology of the redundancy management for a duplex FBW flight control system is introduced. A statistical analysis is applied to determine two design parameters in CCM(Cross Channel Monitor), threshold and persistence count. An analytic redundancy, which is implemented using a Kalman filtering algorithm is considered. The application of an analytic redundancy to the FCS design of the smart UAV has several advantages of increasing the aircraft's survivability and breaking the tie-condition for a duplex FCS. All the redundancy management algorithms are verified through the numeric simulation for the flight dynamics of the XV-15 tilt rotor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.8
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• pp.26-33
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• 2005

Smart UAV, which adopting tiltrotor aircraft concept, requires vertical take-off and landing, long endurance and high speed capability. These contradictable flight performances are hard to meet unless the operation of flap system which should reveal optimal performance for each flight mode. In order to design SUAV flaperon satisfying the three performance requirements, various configurations are generated and their aerodynamic performances are analyzed using numerical flow computations around flap systems. Considering aerodynamic performance and structural simplicity, a final flap configuration is selected and the performance is validated through the wind tunnel testing for 40% scale model.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.