이관중 교수
Kwan-Jung Lee
서울대학교 항공우주공학과 · 공학
연구실 소개
이 교수의 연구실은 항공우주 분야의 설계 및 성능 최적화를 중심으로, 고도화된 수치 해석 기법과 저차원 모델링 기술을 접목한 연구를 수행합니다. 특히, 항공기 및 eVTOL의 초음속·고속 비행 조건에서의 유동 해석, Gurney 플랩 등 부품의 기계적· aerodynamic 특성 분석, 그리고 다중역할 드론의 성능 예측 및 불확실성 전파 분석에 초점을 맞추고 있습니다. 최근에는 딥러닝 기반 저차원 모델링과 전지 설계 최적화 기법을 활용한 실시간 설계 지원 체계 개발에도 기여하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Abstract The inverse approach is computationally efficient in aerodynamic design as the desired target performance distribution is prespecified. However, it has some significant limitations that prevent it from achieving full efficiency. First, the iterative procedure should be repeated whenever the specified target distribution changes. Target distribution optimization can be performed to clarify the ambiguity in specifying this distribution, but several additional problems arise in this proces
In the present study, the aerodynamic characteristics of the Gurney flap were comprehensively investigated in terms of the performance requirements for a helicopter rotor by using two-dimensional Navier-Stokes equations. To this end, with the rotor operating flow conditions in mind, the static aerodynamic characteristics of the Gurney flap are thoroughly compared with those of the clean airfoil at various Mach numbers, incidences, and Gurney flap heights. Next, to understand the general dynamic
Autoencoder-based reduced-order modeling (ROM) has recently attracted significant attention, owing to its ability to capture underlying nonlinear features. However, two critical drawbacks severely undermine its scalability to various physical applications: entangled and therefore uninterpretable latent variables (LVs) and the blindfold determination of latent space dimension. In this regard, this study proposes the physics-aware ROM using only interpretable and information-intensive LVs extracte
This paper focuses on the uncertainty propagation in the flight performance of multirotor-type unmanned aerial vehicles from the systematic perspective in conceptual design phase. The multirotor performance is estimated by a conceptual design and analysis framework which is capable of predicting the performance for given mission profiles and multirotor specifications. In this study, not only are parametric uncertainties considered in multirotor components such as rotor, motor and battery, but al
Recently, electric vertical takeoff and landing (eVTOL) aircraft have garnered significant interest as a primary mode of transportation in advanced air mobility (AAM). For the conceptual design of eVTOL aircraft, where a broad design space must be explored rapidly, a practical and reliable battery sizing process is essential. This process needs to employ models with low computational cost while comprehensively considering two key factors: voltage drop characteristics and thermal effects. However
Snow accumulation on the undercarriage of a train is an important issue that significantly degrades the safety and performance of the vehicle. This phenomenon is primarily attributed to snow saltation induced by train-generated wind gusts. This study numerically investigated the snow accumulation on a train by modelling the snow saltation for the initial movement of drifting snow from the ground. A semi-empirical snow saltation model was applied to the boundary condition for a snow-covered groun
In recent years, the technical advancement of electric propulsion systems has contributed to the growing applicability of multirotor-type unmanned aerial vehicles from personal hobbies to industrial fields. Industrial fields involve various mission profiles comprising several mission-legs, such as hover and forward flight. Thus, enhancing the applicability of multirotors requires them to be designed for specific mission profiles. This paper presents systematic design and analysis methods for rea
Abstract The use of non‐intrusive reduced order modeling (NIROM) to approximate high‐fidelity computer models has been steadily increased over the past decade. Recently, local NIROM has been proposed to improve the model accuracy in highly nonlinear problems in which distinct characteristic regimes coexist. The core concept of local NIROM is the decomposition of the parameter domains into a subregime to create multiple models. However, the existing local NIROM not only partitions the individual
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