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NACA0015 익형의 압력항력 감소를 위한 인공신경망 기반의 피드백 유동 제어

Feedback Flow Control Using Artificial Neural Network for Pressure Drag Reduction on the NACA0015 Airfoil

  • Baek, Ji-Hye (Department of Aerospace Information Engineering, Konkuk University) ;
  • Park, Soo-Hyung (Department of Mechanical and Aerospace Engineering, Konkuk University)
  • 투고 : 2021.05.20
  • 심사 : 2021.07.14
  • 발행 : 2021.09.01

초록

본 연구에서는 실속 받음각 근처에 발생하는 익형 위의 유동박리를 억제하기 위하여 인공신경망 기반의 피드백 유동제어를 NACA0015 익형에 수치적으로 적용하였다. 익형 위 박리영역 크기의 축소화라는 제어 목표를 달성하기 위해 익형의 박리 지점 근처에 인위적 외란(Blowing & Suction) 제어 신호를 적용하였다. 유동의 운동을 나타내는 시스템 모델링 단계에서 압력데이터에 적합직교분해(Proper Orthogonal Decomposition)를 적용하여 유동제어에 필요한 운동 모드를 추출하고 유동의 특성을 분석하였다. 분해된 모드를 기반으로 NARX(Nonlinear AutoRegressive Exogenous) 구조의 인공 신경망을 학습하여 유동의 운동을 나타내도록 하였으며, 최종적으로 피드백 제어루프에 작동시켰다. 예측된 제어신호를 CFD 해석에 적용하였으며 제어 유/무에 따른 공력특성을 분석하고 익형 주변의 고유 공간모드의 변화를 비교하여 제어 효과를 분석하였다. 본 연구에서 진행된 피드백 제어는 약 29%의 압력항력 감소효과를 보여주었으며, 이는 익형 뒷전의 큰 압력회복으로 인해 나타나는 것을 확인하였다.

Feedback flow control using an artificial neural network was numerically investigated for NACA0015 Airfoil to suppress flow separation on an airfoil. In order to achieve goal of flow control which is aimed to reduce the size of separation on the airfoil, Blowing&Suction actuator was implemented near the separation point. In the system modeling step, the proper orthogonal decomposition was applied to the pressure field. Then, some POD modes that are necessary for flow control are extracted to analyze the unsteady characteristics. NARX neural network based on decomposed modes are trained to represent the flow dynamics and finally operated in the feedback control loop. Predicted control signal was numerically applied on CFD simulation so that control effect was analyzed through comparing the characteristic of aerodynamic force and spatial modes depending on the presence of the control. The feedback control showed effectiveness in pressure drag reduction up to 29%. Numerical results confirm that the effect is due to dramatic pressure recovery around the trailing edge of the airfoil.

키워드

과제정보

이 논문은 0000년도 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No.2021R1A5A1031868).

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