• Title/Summary/Keyword: TiltRotor

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A Study on Performance Diagnostic of Smart UAV Gas Turbine Engine using Neural Network (신경회로망을 이용한 스마트 무인기용 가스터빈 엔진의 성능진단에 관한 연구)

  • Kong Chang-Duk;Ki Ja-Young;Lee Chang-Ho;Lee Seoung-Hyeon
    • 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.

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A Study on Compressor Map Identification using Artificial Intelligent Technique and Performance Deck Data (인공지능 및 성능덱 데이터를 이용한 압축기 성능도 식별에 관한 연구)

  • Kong Chang-Duck;Ki Ja-Young;Lee Chang-Ho
    • 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.

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A Study on Fault Detection of Main Component for Smart UAV Propulsion system (스마트 무인기 추진시스템의 주요 구성품 손상 탐지에 관한 연구)

  • Kong, Chang-Duk;Kim, Ju-Il;Ki, Ja-Young;Kho, Seong-Hee;Choe, In-Soo;Lee, Chang-Ho
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2006.11a
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    • pp.281-284
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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). The measurement parameters of Smart UAV propulsion system are gas generator rotational speed, power turbine rotational speed, exhaust gas temperature and torque. But two measurement such as compressor exit pressure and compressor turbine exit temperature were added because they were difficult each component diagnostics using the default measurement parameter. The performance parameters for the estimate of component performance degradation degree are flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network learning 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 could detect well the single fault types such as compressor fouling and compressor turbine erosion.

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Computation of Energy Release Rates for Slender Beam through Recovery Analysis and Virtual Crack Closure Technique (차원 복원해석과 가상균열닫힘 기법을 이용한 종방향 균열을 가진 세장비가 큰 보의 에너지 해방률 계산)

  • Jang, Jun Hwan;Koo, Hoi-Min;Ahn, Sang Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.30 no.1
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    • pp.31-37
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    • 2017
  • In this paper, computation results of reducible modeling, stress recovery and energy release rate were compared with the results of VABS, Virtual Crack Closure Technique. The result of stress recovery analysis for 1-D model including the stiffness matrix is compared with stress results of three-dimensional 3-D FEM. Energy release rate of composite beam with longitudinal cracks is calculated and compare verifications of numerical analysis results of 3-D FEM and VABS. The procedure of calculating energy release rate through dimensional reduction and stress recovery is intended to be efficient and be utilized in the life-cycle of high-altitude uav's wing, wind blades and tilt rotor blade.

Flow Control of Smart UAV Airfoil Using Synthetic Jet Part 2 : Flow control in Transition Mode Using Synthetic Jet (Synthetic jet을 이용한 스마트 무인기(SUAV) 유동제어 Part 2 : 천이 비행 모드에서 synthetic jet을 이용한 유동제어)

  • Kim, Min-Hee;Kim, Sang-Hoon;Kim, Woo-Re;Kim, Chong-Am;Kim, Yu-Shin
    • 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.

Flow Control of Smart UAV Airfoil Using Synthetic Jet Part 1 : Flow control in Hovering Mode Using Synthetic Jet (Synthetic jet을 이용한 스마트 무인기(SUAV) 유동제어 Part 1 : 정지 비행 모드에서 synthetic jet을 이용한 유동제어)

  • Kim, Min-Hee;Kim, Sang-Hoon;Kim, Woo-Re;Kim, Chong-Am;Kim, Yu-Shin
    • 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.

A Study on Performance Diagnostic of Smart UAV Gas Turbine Engine using Neural Network (신경회로망을 이용한 스마트 무인기용 가스터빈 엔진의 성능진단에 관한 연구)

  • Kong Chang-Duk;Ki Ja-Young;Lee Chang-Ho
    • 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.

A Study on Compressor Map Identification using Artificial Intelligent Technique and Performance Deck Data (인공지능 및 성능덱 데이터를 이용한 압축기 성능도 식별에 관한 연구)

  • Ki Ja-Young;Kong Chang-Duck;Lee Chang-Ho
    • 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.

Initial Cycle Design of a 100hp class Turboshaft Engine with a Recuperator (레큐퍼레이터 장착형 100마력급 터보샤프트엔진의 초기 싸이클 설계)

  • Jun, Yongmin;Kim, Jaehwan
    • 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.

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A study on the Development Direction of Unmanned Systems for Subterranean Operations for the Special Operations Teams (특수작전팀의 지하작전용 무인체계 발전방향 연구)

  • Sang-Keun Cho;Jong-Hoon Kim;Sung-Jun Park;Bum-June Kwon;Ga-Ram Jeong;Sang-Hyuk Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.2
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    • pp.307-312
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    • 2023
  • North Korea has already been using underground space for military purposes for decades, and is currently developing it as a key base for operating asymmetric forces. Accordingly, the special operations teams need fighting methods, weapon systems, and organizational structures to carry out subterranean operations. This paper presents an unmanned system platform for subterranean operations that combines tilt-rotor type drones, high-tech sensors, communication repeaters, and small robots, and a system that can be operated by special operation teams. Based on this, the survivability of the special operations teams can be strengthened and operational utility can be maximized. Afterwards, if Special Warfare Command collects collective intelligence based on the ideas related to subterranean operations presented in this paper and further develops these, it will be possible to drive subterranean operations doctrines, weapon systems, and organizational structures optimized for the battlefield on the Korean Theater of Operations in the near future.