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    A Study on Optimal Array Configuration of Tidal Stream Turbine Farm based on Actuator Disc Modeling

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : κ³΅κ³ΌλŒ€ν•™ κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€, 2019. 2. ν™©μ§„ν™˜.μ‘°λ₯˜μ—λ„ˆμ§€λŠ” 지속가λŠ₯ν•œ λŒ€μ²΄μ—λ„ˆμ§€ μ€‘μ—μ„œλ„ μ˜ˆμΈ‘κ°€λŠ₯ν•œ νŠΉμ„±μœΌλ‘œ 인해 각광받고 μžˆλ‹€. μ‘°λ₯˜λ°œμ „λ‹¨μ§€λŠ” λͺ©ν‘œ μ „λ ₯λŸ‰ 확보λ₯Ό μœ„ν•΄ λ°±λŒ€ μ΄μƒμ˜ ν„°λΉˆμœΌλ‘œ κ΅¬μ„±ν•˜κΈ° λ•Œλ¬Έμ— λ°°μ—΄μ˜ μ΅œμ ν™”κ°€ ν•„μˆ˜μ μ΄λ‹€. 비둝 μ‹€μ œ μ‘°κ±΄μ—μ„œμ˜ 졜적 배열은 λ°”λ‹₯μ§€ν˜• 및 μ œν•œλœ κ°€μš© ꡬ역 등에 큰 영ν–₯을 λ°›μœΌλ‚˜, μ‘°λ₯˜μ—λ„ˆμ§€ λΆ€μ‘΄λŸ‰ μ‚°μ •κ³Όμ •μ—μ„œ μ‚¬μš©κ°€λŠ₯ν•œ μ •ν˜•ν™”λœ 졜적 배열에 κ΄€ν•œ 연ꡬ가 ν•„μš”ν•œ 싀정이닀. λ˜ν•œ μ‹€μ œ 배열을 섀계할 λ•ŒλŠ” μ‘°λ₯˜λ°œμ „λ‹¨μ§€μ˜ νŠΉμ„±μƒ 경사도 기반 μ΅œμ ν™”κ°€ λΆˆκ°€ν”Όν•œλ°, 경사도 기반 μ΅œμ ν™”μ˜ ν•΄λŠ” μ΄ˆκΈ°λ°°μ—΄μ‘°κ±΄μ— 따라 ꡭ지 μ΅œμ ν•΄λ‘œ μˆ˜λ ΄ν•  κ°€λŠ₯성이 λ†’κΈ° λ•Œλ¬Έμ— μ „μ—­ μ΅œμ ν•΄μ— κ°€κΉŒμš΄ μ΄ˆκΈ°μ‘°κ±΄μ„ μ‚¬μš©ν•  ν•„μš”κ°€ μžˆλ‹€. λ”°λΌμ„œ λ³Έ μ—°κ΅¬λŠ” μ—¬λŸ¬κ°€μ§€ μ œν•œμ‘°κ±΄μ— λŒ€ν•˜μ—¬ 2차원 μ‘°λ₯˜λ°œμ „단지 λ°°μ—΄μ˜ μ •ν˜•ν™”λœ μ΅œμ ν•΄λ₯Ό μ œμ‹œν•˜κ³ μž ν•œλ‹€. λͺ©μ ν•¨μˆ˜μΈ 총 μ—λ„ˆμ§€ μΆ”μΆœλŸ‰μ„ κ΅¬μ†ν•˜λŠ” νŽΈλ―ΈλΆ„ 방정식은 2차원 μ •μƒμƒνƒœ μ²œμˆ˜λ°©μ •μ‹μ„ μ‚¬μš©ν•˜μ—¬ μ‘°λ₯˜ν„°λΉˆμ— μ˜ν•œ μ‘°λ₯˜νλ¦„μ˜ λΉ„μ„ ν˜•μ μΈ λ³€ν™”λ₯Ό λ°˜μ˜ν•  수 μžˆλ„λ‘ ν•˜μ˜€λ‹€. μ²œμˆ˜λ°©μ •μ‹ 솔버와 μ΅œμ ν™”λ₯Ό μ»€ν”Œλ§ν•˜λŠ” ν”„λ‘œκ·Έλž¨μœΌλ‘œλŠ” 파이썬 기반 μ˜€ν”ˆμ†ŒμŠ€ μ†Œν”„νŠΈμ›¨μ–΄μΈ OpenTidalFarm을 μ‚¬μš©ν•˜μ˜€λ‹€. μ‘°λ₯˜ν„°λΉˆμ€ 앑츄에이터 λ””μŠ€ν¬λ‘œμ¨ λͺ¨λΈλ§ ν•˜μ˜€κ³ , λ‹€μ–‘ν•œ μ„ ν–‰μ—°κ΅¬μ—μ„œ μ œμ‹œν•œ ν›„λ₯˜μ˜ μœ μ† λ³€ν™”λ₯Ό κ°€μž₯ λΉ„μŠ·ν•˜κ²Œ λͺ¨μ˜ν•˜λŠ” λ―Έμ •κ³„μˆ˜λ“€μ˜ 쑰합을 μ°Ύμ•„ μ‘°λ₯˜ λͺ¨λΈλ§μ— μ‚¬μš©ν•˜μ˜€λ‹€. λ‹€λ³€μˆ˜ ν•¨μˆ˜μ˜ 경사도 기반 μ΅œμ ν™”λŠ” μ „μ—­ μ΅œλŒ“κ°’μ΄ μ•„λ‹Œ μ΄ˆκΈ°μ‘°κ±΄μ— 따라 λ‹€λ₯Έ ꡭ지 κ·ΉλŒ“κ°’μœΌλ‘œ μˆ˜λ ΄ν•˜κΈ° λ•Œλ¬Έμ— 이상화 된 μ‘°λ₯˜ν•΄ν˜‘에 λ‹€μ–‘ν•œ μ΄ˆκΈ°λ°°μ—΄μ‘°κ±΄μ„ μ μš©ν•΄ μ—¬λŸ¬ ꡭ지 μ΅œμ ν•΄ 쀑 κ°€μž₯ 좜λ ₯λŸ‰μ΄ 높은 λ°°μ—΄μ˜ ν˜•νƒœλ₯Ό μ°Ύμ•˜λ‹€. 수치λͺ¨μ˜ κ²°κ³Ό κ°€λŠ₯ν•˜λ‹€λ©΄ κ°€μš©μ˜μ—­μ˜ 폭 전체에 걸쳐 λ“±κ°„κ²©μœΌλ‘œ 배치된 μ„ ν˜• 보 ν˜•νƒœμ˜ 배열이 μ΅œμ ν˜•νƒœλ‘œ λ‚˜νƒ€λ‚¬λ‹€. ν•˜μ§€λ§Œ ν„°λΉˆκ°„ μ΅œμ†Œκ°„κ²© 쑰건과 κ°€μš©μ˜μ—­ 폭 λ“±μ˜ μ œν•œμ‘°κ±΄λ“€μ— μ˜ν•΄ μœ„μ™€ 같은 배열이 λΆˆκ°€λŠ₯ν•˜λ‹€λ©΄ 곑λ₯ μ„ κ°–λŠ” 보 ν˜•νƒœλ‚˜, 더 λ‚˜μ•„κ°€ V ν˜• 보 ν˜•νƒœμ˜ 배열이 μ΅œμ ν˜•νƒœλ‘œ λ‚˜νƒ€λ‚¬λ‹€. μ΄λŠ” ν„°λΉˆ 배열이 μ‘°λ₯˜λ₯Ό 폭방ν–₯으둜 κ°€λ‘œλ§‰λŠ” ν˜•νƒœκ°€ νš¨μœ¨μ μ΄λΌλŠ” 것을 μ˜λ―Έν•˜λ©°, μ‚°μΆœκ°€λŠ₯ν•œ μ—λ„ˆμ§€λ₯Ό κ³„μ‚°ν•œ κ²°κ³Ό 같은 개수의 ν„°λΉˆμ„ μ„œλ‘œ 영ν–₯을 주지 μ•Šλ„λ‘ λ…λ¦½μ μœΌλ‘œ λ°°μΉ˜ν–ˆμ„ λ•Œ 얻을 수 μžˆλŠ” μ—λ„ˆμ§€λ³΄λ‹€ μ΅œλŒ€ 30% 이상 νš¨μœ¨μ μ΄λ‹€. λ˜ν•œ 같은 개수의 ν„°λΉˆμ˜ μ΅œμ λ°°μ—΄μ΄ μ‘°λ ₯λ°œμ „λ‹¨μ§€ μ„€κ³„μ‹œ μ œν•œμ‘°κ±΄ (ν„°λΉˆκ°„μ˜ μ΅œμ†Œ 간격, κ°€μš© κ΅¬μ—­μ˜ 폭 μ œν•œ λ“±)에 μ˜ν•΄ μ—λ„ˆμ§€ 좜λ ₯λŸ‰μ΄ μ΅œλŒ€ 50%κΉŒμ§€ 차이가 λ°œμƒν•  수 μžˆμŒμ„ ν™•μΈν•˜μ˜€λ‹€. μ΄λŸ¬ν•œ κ²°κ³ΌλŠ” 효율적인 μ‘°λ ₯λ°œμ „λ‹¨μ§€λ₯Ό μ„€κ³„ν•˜κΈ° μœ„ν•΄μ„œλŠ” λ‹¨μˆœνžˆ 각 μ œν•œμ‘°κ±΄μ—μ„œμ˜ μ΅œμ λ°°μ—΄μ„ μ°ΎλŠ” 문제 뿐만 μ•„λ‹ˆλΌ μ μ ˆν•œ μ œν•œμ‘°κ±΄μ„ μ„€κ³„ν•˜λŠ” 문제의 μ€‘μš”μ„±μ„ μ œμ‹œν•œλ‹€. λ³Έ μ—°κ΅¬μ—μ„œ μ œμ‹œν•œ 방법둠은 얕은 μˆ˜μ—­μ—μ„œ μ΅œμ ν•΄μ— κ°€κΉŒμš΄ ν„°λΉˆλ°°μ—΄μ„ μ°ΎκΈ° μœ„ν•œ 합리적인 접근방식이며, ν„°λΉˆμ΄ μ„€μΉ˜λœ μ±„λ„μ˜ 동역학적 νŠΉμ„±μ— κ΄€ν•œ 직관을 μ œκ³΅ν•œλ‹€κ³  ν‰κ°€λœλ‹€.Tidal current energy is a sustainable and predictable renewable energy resource. In tidal farm design, optimization of array configuration is essential as tidal farm is constituted of hundreds of turbines. This study aimed to suggest a generalized optimal array configuration for idealized tidal straits. Due to the strong nonlinear interaction between tidal device and tidal flow, optimizing two-dimensional array position should base on PDE-constrained gradient-based optimization algorithm. PDE is given as two-dimensional nonlinear steady shallow water equation in order to reflect the movement of tidal flow and reduce computational cost. Total power output is the target functional to be maximized, and OpenTidalFarm is used as a tool for coupling PDE solver and optimization algorithm. Turbine was parameterized as an actuator disc. Optimization was undertaken with various situations, such as varying number of deployed turbines N, minimum distance constraint , spanwise farm site constraint and initial conditions. It was found that optimization result is highly dependent on and , and also sensitive to initial condition. Thus, it is recommended to use proper initial condition which resembles optimal array configurations. Analysis on the various case of optimized result (over 100 cases) suggests that linear barrage with uniform spacing can be considered as acceptable optimal array. Furthermore, if linear barrage shape is impossible due to the optimization constraints (such as and ), it was observed that connecting all turbines as a curved or V shaped barrage performs better than splitting the array into two parts. This study highlights the necessity of designing proper site constraints and distance constraints, showing that the performance of optimal array for identical N can vary up to 50% with different constraints. It is expected that this optimal shape of array can be implemented for array design in tidal energy resource assessment or for recommended initial condition in gradient-based optimization.ABSTRACT i Table of Contents iii List of Figures vi List of Tables viii Nomenclature ix Chapter 1. Introduction 1 1.1 Tidal current energy and its assessment 1 1.2 Tidal farm optimization 4 1.3 Necessity of defining generalized configuration of decent tidal array 5 1.4 Aim of the thesis 6 1.4.1 Modeling tidal turbine in 2D Shallow Water using Actuator Disc modeling 7 1.4.2 Finding optimal array configuration via PDE-constrained gradient-based optimization 7 1.4.3 Analyzing the relationship between optimization constraints and optimization results. 8 Chapter 2. Theoretical background 9 2.1 Linear Momentum Actuator Disc Theory (LMADT) 9 2.1.3 Betzs unbounded flow 11 2.3.2 Garrett and Cumminss rigid lid flow 14 2.3.3 Houlsby et al.s free-surface flow 18 2.3.4 Limitations of LMADT 24 2.2 Shallow Water Equation (SWE) 25 2.3 PDE-constrained Gradient-based Optimization using Adjoint method 27 2.3.1 Gradient-based Optimization 28 Chapter 3. Methodology 30 3.1 Specifications of OpenTidalFarm 30 3.1.1 Design Parameters 30 3.1.2 PDE constraint 31 3.1.3 Turbine Parameterisation 31 3.1.4 Target functional 32 3.1.5 Box and inequality constraints 33 3.1.6 Gradient-based optimization with adjoint approach 34 3.2 Realistic Actuator Disc Modeling in 2D SWE 35 3.2.1 Actuator disc modeling in 2D SWE and 3D flow model 36 3.2.2 Wake properties behind tidal turbine 37 3.2.3 Simulation settings for tuning K and 38 3.2.4 Simulation results 44 3.3 Pilot Test 1: effect of initial condition and number of turbines on optimization result 46 3.3.1 Simulation settings 46 3.3.2 Simulation results 49 3.3.3 Conclusions of pilot test 1 49 3.4 Pilot Test 2: effect of minimum distance constraint and spanwise length of the farm site on optimization result 50 3.4.1 Simulation settings 50 3.4.2 Simulation results 52 3.4.3 Conclusions of pilot test 2 55 3.5 Main test: maximum number of turbines which can be considered as a barrage type configuration 56 3.5.1 Simulation settings 56 Chapter 4. Results and Discussions 60 4.1 Analysis on optimal array configuration and tidal farm output 60 4.2 Extracted Power and Nmax 64 4.3 Limitations of the Modeling 65 Chapter 5. Conclusions 68 APPENDIXS 71 Appendix A. 71 Appendix B. 73 Appendix C. 78 REFERENCES 86 ꡭ문초둝 91Maste

    μ‚¬νšŒλ΄‰μ‚¬λͺ…λ Ήμ œλ„μ˜ 집행에 κ΄€ν•œ 연ꡬ

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    ν•™μœ„λ…Όλ¬Έ(석사)--μ„œμšΈλŒ€ν•™κ΅ ν–‰μ •λŒ€ν•™μ› :ν–‰μ •ν•™κ³Ό 행정학전곡,2003.Maste

    κ³„μ ˆμ  κ΄‘ λ³€ν™” 및 인곡 μ‘°λͺ… μ²˜λ¦¬κ°€ μ˜¨μ‹€ 재배 μ•½μ‘₯(Artemisia princeps)의 생μž₯ 및 ν”ŒλΌλ³΄λ…Έμ΄λ“œ 생산에 λ―ΈμΉ˜λŠ” 영ν–₯

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 농업생λͺ…κ³Όν•™λŒ€ν•™ μ›μ˜ˆν•™κ³Ό, 2019. 2. 손정읡.Artemisia princeps (Ganghwa wormwood) is a medicinal plant with two major flavonoids, eupatilin and jaceosidin, which have gastritis and peptic ulcers treatment properties. Until now, the plants are cultivated in the fields which provides one cultivation period, and produces unstable flavonoid contents by environmental changes. The objective of this study was to analyze the effects of seasonal light variation and artificial light treatments on growth and flavonoid production of A. princeps grown under greenhouse conditions for year-round production. From April 2016 to April 2017, nine sets of the plants were cultivated and harvested under natural seasonal light conditions in greenhouses. From September 2016 to January 2017, four additional artificial light treatments were applied for two sets of the plants: supplemental light, night interruption, low light, and low light with night interruption. The plants grown under natural light condition in greenhouses were used as a control. After harvest, plant growth was measured, and the contents of eupatilin and jaceosidin were determined. The plants had the highest biomass when the accumulated radiation and duration were highest. Plant growth and flavonoid production were significantly associated with accumulated radiation and light duration. Supplemental light and night interruption treatments resulted in significantly higher biomass and flavonoid production. For consistent biomass and flavonoid production of A. princeps, night interruption treatment is suggested in greenhouse cultivation during low irradiation and short days (less than 13 h).Artemisia princeps(κ°•ν™”μ•½μ‘₯)은 μœ„κΆ€μ–‘ 및 μœ„κ²½λ ¨ 치료의 νŠΉμ„±μ„ 가지고 μžˆλŠ” ν”ŒλΌλ³΄λ…Έμ΄λ“œ μœ νŒŒν‹Έλ¦°κ³Ό μžμ„Έμ˜€μ‹œλ”˜μ„ ν•¨μœ ν•˜κ³  μžˆλ‹€. 일반적으둜 λ…Έμ§€μ—μ„œ 연쀑 1회 재배되며 ν™˜κ²½ 변화에 따라 ν”ŒλΌλ³΄λ…Έμ΄λ“œ ν•¨λŸ‰μ΄ λΆˆμ•ˆμ •ν•˜λ‹€. λ³Έ μ—°κ΅¬μ˜ λͺ©μ μ€ κ°•ν™”μ•½μ‘₯의 연쀑 μ•ˆμ •μ μΈ μ˜¨μ‹€ 재배λ₯Ό μœ„ν•΄ κ³„μ ˆμ μΈ κ΄‘ 쑰건 변화와 인곡 μ‘°λͺ… μ²˜λ¦¬μ— λŒ€ν•œ μ‹λ¬Όμ˜ 생μž₯κ³Ό ν”ŒλΌλ³΄μ΄λ…Έμ΄λ“œ ν•¨λŸ‰ λ³€ν™”λ₯Ό λΆ„μ„ν•˜λŠ” 것이닀. 연쀑 총 9회의 재배 μž‘κΈ°λ‘œ μ˜¨μ‹€μ˜ κ³„μ ˆμ μΈ κ΄‘ 쑰건 ν•˜μ—μ„œ μž¬λ°°ν•˜μ˜€λ‹€. κ΄‘ 쑰건의 λ³€ν™”κ°€ 크게 λ‚˜νƒ€λ‚˜λŠ” 겨울철 2회의 μž‘κΈ° μ€‘μ—λŠ” 인곡 μ‘°λͺ… 처리 μΆ”κ°€λ‘œ 보광, μ•ΌνŒŒ, μ €κ΄‘ 및 μ•ΌνŒŒ μ‘°κ±΄μ—μ„œ μž¬λ°°ν•˜μ˜€λ‹€. μˆ˜ν™• ν›„, μ‹λ¬Όμ˜ 생μž₯을 μΈ‘μ •ν•˜κ³ , μœ νŒŒν‹Έλ¦°κ³Ό μžμ„Έμ˜€μ‹œλ”˜μ˜ ν•¨λŸ‰μ„ λΆ„μ„ν•˜μ˜€λ‹€. λˆ„μ  μΌμ‚¬λŸ‰κ³Ό λˆ„μ  일μž₯이 λ†’μ„μˆ˜λ‘ μ‹λ¬Όμ˜ 생μž₯이 μ’‹μ•˜μœΌλ©°, 생μž₯κ³Ό ν”ŒλΌλ³΄λ…Έμ΄λ“œ ν•¨λŸ‰μ€ λˆ„μ  μΌμ‚¬λŸ‰κ³Ό λˆ„μ  일μž₯κ³Ό μœ μ˜ν•œ 관계λ₯Ό λ³΄μ˜€λ‹€. 보광 및 μ•ΌνŒŒ 처리둜 인해 생μž₯κ³Ό ν”ŒλΌλ³΄λ…Έμ΄λ“œ ν•¨λŸ‰μ΄ ν˜„μ €νžˆ λ†’κ²Œ λ‚˜νƒ€λ‚¬λ‹€. 일μž₯이 13μ‹œκ°„ μ΄ν•˜μΈ κ²¨μšΈμ² μ— 총 생μž₯κ³Ό ν”ŒλΌλ³΄λ…Έμ΄λ“œ ν•¨λŸ‰ ν–₯상을 μœ„ν•΄ μ˜¨μ‹€ 재배 μ‹œ μ•ΌνŒŒ 처리둜 생산 μ¦λŒ€μ™€ 연쀑 μ•ˆμ •μ μΈ 생산이 κ°€λŠ₯ν•˜λ‹€κ³  νŒλ‹¨λœλ‹€.ABSTRACT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i CONTENTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii LIST OF TABLES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv LIST OF FIGURES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 LITERATURE REVIEW. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Pharmaceutical uses of A. princeps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Flavonoids and environment conditions. . . . . . . . . . . . . . . . . . . . . . . . . . 4 Medicinal plant cultivation in controlled environments. . . . . . . . . . . . . . .5 MATERIALS AND METHODS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6 RESULTS AND DISCUSSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 CONCLUSIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 LITERATURE CITED. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 ABSTRACT IN KOREAN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36Maste

    A Study on the Categorical Spectrum and Function of Bound Noun in Korean

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    ν•™μœ„λ…Όλ¬Έ(석사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : μΈλ¬ΈλŒ€ν•™ κ΅­μ–΄κ΅­λ¬Έν•™κ³Ό, 2022. 8. λ¬Έμˆ™μ˜.λ³Έ μ—°κ΅¬λŠ” 의쑴λͺ…μ‚¬μ˜ 단어 λΆ€λ₯˜λ‘œμ„œμ˜ 속성과 의쑴λͺ…μ‚¬μ˜ 뢄포에 λ”°λ₯Έ κΈ°λŠ₯을 λ°νžˆλŠ” 것을 λͺ©μ μœΌλ‘œ ν•œλ‹€. 2μž₯μ—μ„œλŠ” 단어 λΆ€λ₯˜λ‘œμ„œμ˜ 의쑴λͺ…μ‚¬μ˜ 속성에 λŒ€ν•΄ λ…Όμ˜ν•˜μ˜€λ‹€. λ¨Όμ € ν˜„λŒ€ ν•œκ΅­μ–΄ 의쑴λͺ…μ‚¬μ˜ λͺ©λ‘μ„ μƒμ„Ένžˆ 밝히고, 의쑴λͺ…μ‚¬μ˜ 인접 범주인 μ–΄λ―Έ, 쑰사, λ³΄μ‘°μš©μ–Έ, μ ‘λ―Έμ‚¬μ™€μ˜ 관계λ₯Ό μ‚΄νŽ΄λ³΄μ•˜λ‹€. λ‹€μŒμœΌλ‘œλŠ” 전톡적인 ν’ˆμ‚¬ λΆ„λ₯˜ 기쀀에 λ”°λ₯Έ 의쑴λͺ…μ‚¬μ˜ 속성을 밝히고 이λ₯Ό 일반적인 λͺ…μ‚¬μ˜ 속성과 λΉ„κ΅Β·λŒ€μ‘°ν•˜μ˜€λ‹€. 의쑴λͺ…μ‚¬λŠ” λͺ…μ‚¬μ˜ 속성을 가지고 μžˆμ§€λ§Œ, κ·Έ μ œμ•½μ΄ μ‹¬ν•œ λΆ€λ₯˜μΈλ°, 의쑴λͺ…μ‚¬μ˜ κ·ΈλŸ¬ν•œ 츑면을 μ˜μ‘΄μ„±κ³Ό 쑰사 및 μ„±λΆ„ μ œμ•½, μ„œμˆ μ–΄ μ œμ•½, λ‚΄μš©μ–΄μ™€ κΈ°λŠ₯μ–΄μ™€μ˜ 비ꡐλ₯Ό 톡해 μ•Œμ•„λ³΄μ•˜λ‹€. λ˜ν•œ, 의쑴λͺ…μ‚¬λŠ” κ²°ν•© μ œμ•½μ— 따라 νŠΉμ΄ν•œ 뢄포λ₯Ό λ³΄μ΄λŠ”λ°, 의쑴λͺ…μ‚¬μ˜ 뢄포λ₯Ό 쑰사λ₯Ό μ€‘μ‹¬μœΌλ‘œ λΆ„λ₯˜ν•˜κ³  의쑴λͺ…μ‚¬μ˜ κΈ°λŠ₯에 λŒ€ν•΄ κ°„λž΅ν•˜κ²Œ μ‚΄ν”Όμ—ˆλ‹€. 3μž₯μ—μ„œλŠ” 2μž₯의 λΆ„λ₯˜μ— μ˜κ±°ν•˜μ—¬ 쑰사 결합에 μ œμ•½μ΄ 적은 의쑴λͺ…사(보편적 의쑴λͺ…사)의 κΈ°λŠ₯κ³Ό 뢄포λ₯Ό μ‚΄ν”Όμ—ˆλ‹€. 보편적 의쑴λͺ…μ‚¬λŠ” 주둜 λŒ€μš© 및 μ§€μ‹œ κΈ°λŠ₯을 μˆ˜ν–‰ν•œλ‹€. 의쑴λͺ…사에 따라 νŠΉμ •ν•œ λŒ€μš© 및 μ§€μ‹œμ— κΈ°λŠ₯이 ν•œμ •λ˜λŠ” 것도 있고 μ—¬λŸ¬ λŒ€μƒμ„ λŒ€μš© 및 μ§€μ‹œν•˜λŠ” κ²ƒμœΌλ‘œ κΈ°λŠ₯이 ν™•μž₯λ˜λŠ” 것도 μžˆλ‹€. ν•œνŽΈ 쑰사 결합에 μ œμ•½μ΄ 적은 의쑴λͺ…사라고 ν•˜λ”λΌλ„ μ„ ν–‰ν•˜λŠ” κ΄€ν˜•μ–΄μ˜ μ’…λ₯˜λ‚˜ μ‹œμ œ κ²°ν•© 등에 μ œμ•½μ„ 보이기도 ν•˜λŠ”λ° μ΄λŸ¬ν•œ 의쑴λͺ…μ‚¬μ˜ 뢄포λ₯Ό μ‘°μ‚¬ν•¨μœΌλ‘œμ¨ 보편적 의쑴λͺ…μ‚¬μ˜ 톡사적 νŠΉμ§•μ„ μ‚΄νŽ΄λ³΄μ•˜λ‹€. 4μž₯μ—μ„œλŠ” 쑰사 결합에 μ œμ•½μ΄ μ‹¬ν•œ 의쑴λͺ…사(μ œν•œμ  의쑴λͺ…사)의 κΈ°λŠ₯κ³Ό 뢄포λ₯Ό μ‚΄ν”Όμ—ˆλ‹€. μ œν•œμ  의쑴λͺ…사듀은 λ¬Έμž₯μ—μ„œ ꡬ성을 이루어 문법적 κΈ°λŠ₯을 μˆ˜ν–‰ν•˜λŠ”λ° 이와 κ΄€λ ¨λœ 문법적 κΈ°λŠ₯μœΌλ‘œλŠ” μ—°κ²°, μ–‘νƒœ, 상, μ§€μ‹œ 및 λŒ€μš©μ΄ μžˆλ‹€. 각 κΈ°λŠ₯을 κ°„λž΅νžˆ μ •λ¦¬ν•˜κ³  κΈ°λŠ₯별 의쑴λͺ…사 κ΅¬μ„±μ˜ 뢄포λ₯Ό μ‘°μ‚¬ν•¨μœΌλ‘œμ¨ μ œν•œμ  의쑴λͺ…μ‚¬μ˜ 톡사적 νŠΉμ§•μ„ μ œμ‹œν•˜μ˜€λ‹€. λ˜ν•œ 같은 의미λ₯Ό ν‘œν˜„ν•˜λŠ” 의쑴λͺ…사라 ν•˜μ—¬λ„ 세뢀적인 νŠΉμ§•μ—λŠ” 차이가 μžˆμ—ˆλŠ”λ° 비ꡐ와 λŒ€μ‘°λ₯Ό 톡해 μ΄λŸ¬ν•œ 차이λ₯Ό λ°νžˆμ—ˆλ‹€. 5μž₯은 κ²°λ‘  λΆ€λΆ„μœΌλ‘œ μ΄μƒμ˜ λ‚΄μš©μ„ μš”μ•½ 및 μ •λ¦¬ν•˜κ³ , λ―Έμ§„ν•œ 점을 밝히며 λ…Όμ˜λ₯Ό λ§ˆλ¬΄λ¦¬ν•˜μ˜€λ‹€.This study aims to identify the attributes of bound nouns as a class of words and their functions according to distribution. In Chapter 2, the study discusses the attributes of Bound nouns as word classes. First, the modern Korean bound morphemes are listed in detail, and the relation with the adjacent categories, such as ending, particle, auxiliary verb, and suffix, are observed. Next, the attributes of bound morphemes by the traditional criteria of parts of speech are addressed, followed by comparison and contrast with those of general nouns. Bound nouns have the attributes of nouns, but are unique in that they have many restrictions, which are discussed through boundness, particle and component restrictions, verb restrictions, and comparison with content words and function words. Further, bound nouns have interesting distribution depending on the conjugation restrictions, which is addressed in this paper by classifying the distribution of bound nouns by particle and briefly observing the functions of bound nouns. In Chapter 3, based on the distribution of bound nouns, the paper addresses the functions and distribution of bound nouns with least limitations with particle conjugation. It also addresses the functions of substitute and reference that the universal bound nouns serve. Meanwhile, even though dependent nouns have fewer restrictions in particle conjugation, there are restrictions in conjugation depending on the types of the preceding abdominals and tense. By studying the distribution of such bound nouns, the chapter exposits the syntactic characteristics of universal bound nouns. Chapter 4 discusses the functions and distribution of bound morphemes with more restrictions in particle conjugation. Restrictive bound nouns serve a grammatical function by forming constructions in sentences. Related grammatical functions are reference, substitute, conjunction, modality, and aspect. The chapter suggests the syntactic characteristics of the restrictive bound morphemes by briefly organizing each function and studying the distribution of the nouns by function. Chapter 5, as a conclusion, summarizes and organizes the above discussion and considers limitations.1. μ„œλ‘  1 1.1. 연ꡬ λͺ©μ  1 1.2. μ„ ν–‰ 연ꡬ 3 1.3. 연ꡬ λŒ€μƒ 5 1.4. λ…Όμ˜μ˜ ꡬ성 6 2. 단어 λΆ€λ₯˜λ‘œμ„œμ˜ 의쑴λͺ…μ‚¬μ˜ 속성 8 2.1. 의쑴λͺ…μ‚¬μ˜ λͺ©λ‘κ³Ό 인접 λ²”μ£Ό 8 2.2. ν’ˆμ‚¬ λΆ„λ₯˜ 기쀀에 λ”°λ₯Έ 의쑴λͺ…μ‚¬μ˜ 속성 23 2.3. λͺ…사와 λΉ„κ΅Β·λŒ€μ‘°ν•œ 의쑴λͺ…μ‚¬μ˜ 속성 33 2.3.1. λͺ…μ‚¬μ˜ 속성 33 2.3.2. μ˜μ‘΄μ„± 36 2.3.3. 쑰사 μ œμ•½ 및 μ„±λΆ„ μ œμ•½ 39 2.3.4. μ„œμˆ μ–΄ μ œμ•½ 41 2.3.5. λ‚΄μš©μ–΄μ™€ κΈ°λŠ₯μ–΄μ˜ 쀑간 43 2.4. 뢄포에 μž…κ°ν•œ 의쑴λͺ…μ‚¬μ˜ λΆ„λ₯˜ 50 2.5. 의쑴λͺ…μ‚¬μ˜ κΈ°λŠ₯ 54 3. 보편적 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 61 3.1. β€˜κ²ƒβ€™λ₯˜ 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 62 3.2. β€˜λ“±β€™λ₯˜ 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 65 3.3. β€˜λ‚˜μ ˆβ€™λ₯˜ 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 67 3.4. β€˜μͺ½β€™λ₯˜ 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 69 3.5. β€˜κ²©β€™λ₯˜ 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 72 4. μ œν•œμ  의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 74 4.1. 연결적 의쑴λͺ…사 74 4.1.1. 연결적 의쑴λͺ…μ‚¬μ˜ λΆ„λ₯˜ 74 4.1.2. 연결적 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 78 4.1.2.1. λ‚˜μ—΄ 78 4.1.2.2. λŒ€μ‘° 79 4.1.2.3. 선택 80 4.1.2.4. λ°°κ²½ 81 4.1.2.5. μ„ ν–‰ 83 4.1.2.6. 원인 85 4.1.2.7. λͺ©μ  86 4.2. 상적 의쑴λͺ…사 87 4.2.1. 상적 의쑴λͺ…μ‚¬μ˜ λΆ„λ₯˜ 87 4.2.2. 상적 의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 89 4.2.2.1. 진행상 89 4.2.2.2. μ˜ˆμ •μƒ 92 4.3. μ–‘νƒœμ  의쑴λͺ…사 94 4.3.1. μ–‘νƒœμ  의쑴λͺ…μ‚¬μ˜ λΆ„λ₯˜ 94 4.3.2. μ–‘νƒœμ  의쑴λͺ…μ‚¬μ˜ 뢄포와 κΈ°λŠ₯ 98 4.3.2.1. 인식 μ–‘νƒœ 98 4.3.2.2. λ‹Ήμœ„ μ–‘νƒœ 102 4.3.2.3. 동적 μ–‘νƒœ 104 4.3.2.4. 감정 μ–‘νƒœ 106 4.4. μ§€μ‹œ 및 λŒ€μš©μ  의쑴λͺ…사 108 4.5. 기타 의쑴λͺ…사 109 5. κ²°λ‘  114 μ°Έκ³ λ¬Έν—Œ 122 뢀둝 130 Abstract 134석
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