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Theses (Master's Degree_협동과정 우주시스템전공)

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Adaptive mesh refinement:1||Artificialneuralnetwork:1||Branched feedline:1||carbon/phenolic composite:1||Chemicalkinetics:1||Clustered rocket:1||Computational fluid dynamics:1||deep learning:1||dissolved gas analysis:1||Dynamic Smagorinsky:1||fault diagnosis:1||finite element method:1||free play:1||geometry analysis:1||insect-type flapping wing:1||Large-eddy simulation:1||Laser-Induced Breakdown Spectroscopy (LIBS):1||Longitudinal mode analysis:1||Low-swirl combustor:1||Machinelearning:1||Mineral Analysis:1||Miss-distance:1||molecular dynamics:1||multiscale simulation:1||NASA　EVOLVE 4.0 breakup model:1||numerical simulation:1||Opposed-flowdiffusionflame:1||Optimization Study:1||Patera’s method:1||Plasma Analysi:1||Pogo accumulator:1||Pogo instability:1||power transformer:1||Probability of Collision:1||Satellites:1||silicon carbide:1||Space Exploration:1||Space fragments:1||Space launch vehicle:1||Spark-Induced Breakdown Spectroscopy (SIBS):1||Thermal protection system:1||Turbulence generating plate:1||고장진단:1||곤충 모방형 날갯짓 비행체:1||공급라인 압력 모드:1||광물분석:1||기하학적 해석:1||동역학적 시뮬레이션:1||딥러닝:1||레이저 유도 플라즈마 분광법:1

Issue Date	Title / Author(s) / Citation	File
2023	초소형 인공위성용 FEEP 전기추진 시스템 개발에 관한 연구 권찬얼	view file link
2023	Collision Risk Analysis of a Satellite with Fragments from Break-up of a Space Object 윤정훈	view file link
2023	Numerical Study on Turbulent Flow and Flame Characteristics of Low-Swirl Combustor Depending on Turbulence Generating Plate 전병주	view file link
2022	Machine learning for the representation of chemical kinetics in reactive flows 이정용	view file link
2021-02	Integrated Design of Tailless FWMAV with free play: Approach via Geometry and Numerical Analysis 최재원	view file link
2021-02	Development of Multiscale Simulation Framework for Thermal Protection System Ablation Analysis 박태훈	view file link
2021-02	Pogo Instability Analysis of a Clustered Liquid Rocket with Sophisticated Branch Feedline 유정욱	view file link
2021-02	스파크 유도 플라즈마 분광 시스템의 최적화 개발과 우주탐사용 암석 분석 연구 정재헌	view file link
2021	Deep-Learning-Based Fault Diagnosis Using Dissolved Gas Analysis for Unlabeled Fault Data of Industrial Power Transformers 김선의	view file link