25 research outputs found
์ ๊ธฐ์ด๋งค๋ฐ์์ ์ํ ์ ๊ธฐ์ด์ค์ธต ๋ด์ ๊ณ ์ ํ ๋ฐ์ ํ๊ฒฝ
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ์์ฐ๊ณผํ๋ํ ํํ๋ถ, 2023. 8. ์ ํ๋.Since the electrical double layer (EDL) is where heterogeneous electron transfer occurs, understanding the effects of the electrode-electrolyte interface structure on electrocatalysis is important. The strong electric field (~1E9 V/m) in the EDL offers unique environment for electrochemical reactions by altering the solvation structure and mass transport of redox species. This EDL structure can be the key to complementing the electrocatalyst designing principle which mostly depends on the Sabatier principle alone (Chapter 1). Yet, it is challenging to evaluate the physicochemical properties within EDL.
This thesis corroborates the EDL structure to describe the electrocatalytic activity according to the electrode material, as exemplified in the hydrogen evolution reaction (HER) in an acidic aqueous solution and the bromine reduction reaction in a polybromide ionic liquid. Additionally, it introduces methodologies to evaluate two important properties of the EDL structure: the potential of zero charge (PZC) of electrodes and the reorganization energy. Chapter 2 introduces the methodology to measure the local PZC of electrodes using the scanning electrochemical cell microscopy (SECCM). Applying the SECCM to the high-entropy alloy material library (HEA-ML) revealed that the PZC of the HEA is directly correlated to its elemental composition-weighted average work function and that the HER activity in an acidic electrolyte favors a strong negative electric field in the EDL. Chapter 3 describes the methodology to measure the reorganization energy of the bromine reduction in a polybromide ionic liquid based on the Marcus-Hush-Chidsey electron transfer kinetics theory. Reorganization energy on the platinum surfaces modified with titanium oxide of positive charges suggested the surface-charge dependent solvation structure in the inner Helmholtz plane (IHP), which affects the electron transfer kinetics. Chapter 4 reports a method to evaluate the reorganization energy of the polybromide ionic liquid using the SECCM. This enables the investigation of the reorganization energy on alloys, which are difficult to fabricate into ultramicroelectrodes. Chapter 5 summarizes the dissertation and addresses a future perspective on the EDL engineering as a promising electrocatalyst designing principle.๋ถ๊ท ์ผ ์ ์์ ๋ฌ ๋ฐ์์ด ์ผ์ด๋๋ ์ ๊ทน-์ ํด์ง ๊ณ๋ฉด ๊ตฌ์กฐ์ ๋ฐ์ ํ๊ฒฝ์ ์ดํดํ๋ ๊ฒ์ ํจ์จ์ ์ธ ์ ๊ธฐ์ด๋งค ์ค๊ณ๋ฅผ ์ํด ์ค์ํ๋ค. ํนํ ์ ๊ทน ํ๋ฉด์์ ์~์์ญ nm ๊ฑฐ๋ฆฌ ๊ณต๊ฐ์๋ ์ฝ 1E9 V/m ํฌ๊ธฐ์ ์ ๊ธฐ์ฅ์ด ๊ฑธ๋ ค์๋ ์ ๊ธฐ์ด์ค์ธต์ด ์กด์ฌํ๋ค. ์ ๊ธฐ์ด์ค์ธต์ ๊ฐํ ์ ๊ธฐ์ฅ์ ์ฉ๋งค์ ๋ถ๊ทน์ ์ ๋ํ๊ณ ์ฉ๋งค ๋ฐฐ์ด ๊ตฌ์กฐ๋ฅผ ๋ฐ๊พธ์ด ๋ถ๊ท ์ผ ์ ์์ ๋ฌ ์๋์์ ์์ฒด๋ฅผ ๋ฐ๊ฟ ์ ์์ ๋ฟ ์๋๋ผ, ์ ํ๋ฅผ ๋ค ๋ฐ์์ข
๊ณผ ์์ฑ๋ฌผ์ ๋ฌผ์ง์ ๋ฌ์๋ ์ํฅ์ ์ค ์ ์๋ค. ๊ทธ๋ฌ๋ ๊ณ๋ฉด์ ์ ํธ๋ ๊ณต๊ฐ ํฌ๊ธฐ๊ฐ ํฐ ๋ฒํฌ ์ฉ์ก์ ์ ํธ์ ๋นํด ์ฝํ๋ฉฐ, ๋ฒํฌ ์ ํธ์ ์์ฌ ๋์ค๊ธฐ ์ฝ๋ค๋ ๊ทผ๋ณธ์ ์ธ ์คํ์ ํ๊ณ๋ก ๋ฒํฌ์๋ ๋ค๋ฅธ ์ ๊ธฐ์ด์ค์ธต ๋ด๋ถ์ ๊ณ ์ ํ ์ ์์ ๋ฌ ๋ฐ์ ํ๊ฒฝ์ ๋ํ ์ฐ๊ตฌ๋ ๋๋ ์ํฉ์ด๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ ์ฐ์ฑ ์์ฉ์ก์์์ ์์ ๋ฐ์ ๋ฐ์๊ณผ ์ด์จ์ฑ ์ก์ฒด ๋ด ๋ธ๋ก๋ฏผ ํ์ ๋ฐ์์ ์์๋ก ์ ๊ธฐ์ด์ค์ธต ๊ตฌ์กฐ๊ฐ ์ ๊ทน ์ฌ๋ฃ์ ๋ฐ๋ฅธ ์ ๊ธฐ์ด๋งค ํ์ฑ ๊ฒฝํฅ์ฑ์ ๊ธฐ์ ํ๋๋ฐ ์ค์ํ ๋ณ์์์ ์ ์ํ๋ค. ์ด๋ ๋ฐ์ ์ค๊ฐ์ฒด์ ํก์ฐฉ์๋์ง๊ฐ ์ ๊ธฐ์ด๋งค ๋ฐ์์ฑ์ ๊ฐ์ฅ ์ค์ํ๋ค๋ ์ฌ๋ฐํฐ์ ์๋ฆฌ์๋ง ํฌ๊ฒ ์์กดํด์๋ ์ ๊ธฐ์ด๋งค ์ค๊ณ ์๋ฆฌ๋ฅผ ๋ณด์ํด์ค๋ค. 1์ฅ์์๋ ์ ํต์ ์ธ ์ ๊ธฐ์ด๋งค ์ง์์ ์ด๋ก ์ธ ์ฌ๋ฐํฐ์ ์๋ฆฌ๋ฅผ ์ค๋ช
ํ๊ณ , ์ฌ๋ฐํฐ์ ์๋ฆฌ์ ํ๊ณ์ ๋ค์ ์๊ฐํ๋ค. 2์ฅ์์๋ ์ฃผ์ฌ ์ ๊ธฐํํ ์
ํ๋ฏธ๊ฒฝ ๊ธฐ์ ๊ณผ ๊ณ ์ํธ๋กํผ ํฉ๊ธ ์ฌ๋ฃ ๋ผ์ด๋ธ๋ฌ๋ฆฌ ์ ๊ทน์ ์ด์ฉํ์ฌ ํฉ๊ธ์ ์์ ์กฐ์ฑ์ ๋ฐ๋ฅธ ์ ๊ทน์ ์์ ํ์ ์์ ์์ ๋ฐ์ ๋ฐ์์ฑ์ ์คํฌ๋ฆฌ๋ํจ์ผ๋ก์จ, ๊ณ ์ํธ๋กํผ ํฉ๊ธ์ ์์ ๋ฐ์ ์ ๋ฅ๊ฐ ์ ๊ทน์ ์์ ํ์ ์์ ์์ ์๊ด๊ด๊ณ๊ฐ ์์์ ๋ฐํ๋ค. ๊ณ ์ํธ๋กํผ ํฉ๊ธ์ ์์ ํ์ ์๋ ํฉ๊ธ์ ์์ ์กฐ์ฑ ๊ฐ์ค ํ๊ท ์ผํจ์์ ๊ธฐ์ธ๊ธฐ 1์ ์ ํ ์๊ด๊ด๊ณ๊ฐ ์์๋ค. ๋ณธ ๊ฒฐ๊ณผ๋ ํจ๊ณผ์ ์ธ ์์ ๋ฐ์ ๋ฐ์ ์ ๊ธฐ ์ด๋งค๋ฅผ ์ํ ํฉ๊ธ์ ์์ ์กฐ์ฑ ์ค๊ณ ์๋ฆฌ๋ฅผ ์ ๊ณตํ๋ค. 3์ฅ์์๋ ๋ง์ปค์ค-ํ์ฌ-์น์ง ์ ์์ ๋ฌ ์๋๋ก ์ด๋ก ์ ๊ธฐ๋ฐ์ผ๋ก ํด๋ฆฌ๋ธ๋ก๋ง์ด๋ ์ด์จ์ฑ ์ก์ฒด ๋ด ๋ธ๋ก๋ฏผ ํ์ ๋ฐ์์ ์ฌ๋ฐฐ์ด ์๋์ง๋ฅผ ์ธก์ ํ ์ ์๋ ๋ฐฉ๋ฒ๋ก ์ ๊ฐ๋ฐํ์๋ค. ๋ฐฑ๊ธ ์ ๊ทน ํ๋ฉด์ ์์ ํ๋ฅผ ๋ ๋ ํฐํ๋ ์ฅ์ฌ์ด๋๋ฅผ ๋์
ํ์์ ๋์ ์ฌ๋ฐฐ์ด ์๋์ง ๋ณํ๋ฅผ ํตํด, ์ ๊ทน ํ๋ฉด ์ ํ์ ๋ฌ๋ผ์ง๋ ์ด์จ์ฑ ์ก์ฒด-์ ๊ทน ๊ณ๋ฉด์ ๋ด๋ถ ํฌ๋ฆํ์ธ ์ธต์ ์ฉ๋งคํ ๊ตฌ์กฐ ๋ณํ์ ์ด๋ก ์ธํ ์ ์์ ๋ฌ ๋ฐ์ ์๋ ์์ ๋ณํ์ ๋ํ ๋ชจ๋ธ์ ์ ์ํ ์ ์์๋ค. 4์ฅ์์๋ ์ฃผ์ฌ ์ ๊ธฐํํ ์
ํ๋ฏธ๊ฒฝ์ ์ฌ์ฉํด์ ์ฌ๋ฐฐ์ด ์๋์ง๋ฅผ ์ธก์ ํ๋ ๋ฐฉ๋ฒ๋ก ์ ๋ณด๊ณ ํ์๋ค. ์ด ๋ฐฉ๋ฒ์ ๋ง์ดํฌ๋ก ์ ๊ทน์ผ๋ก ๋ง๋ค๊ธฐ ๊น๋ค๋ก์ด ํฉ๊ธ ์ ๊ทน์์์ ์ฌ๋ฐฐ์ด ์๋์ง๋ฅผ ์ฝ๊ฒ ์กฐ์ฌํ ์ ์๊ฒ ํด์ค๋ค. ๊ท๊ธ์์ผ๋ก ๊ตฌ์ฑ๋ ๊ณ ์ํธ๋กํผ ํฉ๊ธ ์ฌ๋ฃ ๋ผ์ด๋ธ๋ฌ๋ฆฌ์ ์ฌ๋ฐฐ์ด ์๋์ง ์ธก์ ๊ฒฐ๊ณผ๋ 3์ฅ์์ ์ ์ํ ์ ๊ทน ํ๋ฉด ์ ํ์ ๋ฐ๋ฅธ ๋ด๋ถ ํฌ๋ฆํ์ธ ์ธต์ ์ฉ๋งคํ ๊ตฌ์กฐ ๋ณํ ๋ชจ๋ธ์ ๋ท๋ฐ์นจํ๋ค.Abstract i
Contents iii
List of Figures vii
List of Tables xv
Abbreviations xvi
Chapter 1. General Introduction 1
1.1. The Sabatier Principle: To Predict and Explain the Electrocatalytic Activities of a Given Electrode 1
1.2. Limitations of the Sabatier Principle 2
1.3. Mass Transport in the Electrical Double Layer 4
1.4. Microscopic Electron Transfer Kinetics Theory 6
1.5. Aims of Thesis 9
Chapter 2. Acidic Hydrogen Evolution Reaction Activities in High-entropy Alloys Correlates with its Composition Dependent Potential of Zero Charge 11
2.1. Abstract 13
2.2. Introduction 14
2.3. Experimental Methods 17
2.3.1. Materials 17
2.3.2. Electrode Preparation 17
2.3.3. SECCM Tip Preparation 18
2.3.4. SECCM Instrumental Set-up 18
2.3.5. Potential of Zero Charge Determination 20
2.3.6. Hydrogen Evolution Reaction Activity Measurement 22
2.3.7. Finite Element Simulations of the HER Voltammogram 23
2.4. Results and Discussion 27
2.4.1. Measurement of PZC of Pt and Au Surfaces by SECCM 27
2.4.2. PZC Values of a Pt-Pd-Ru-Ir-Ag HEA-ML Evaluated by Means of SECCM 32
2.4.3. Correlation of PZC and HER Electrocatalytic Activities Determined from a Pt-Pd-Ru-Ir-Ag HEA-ML 40
2.4.4. Finite Element Simulation to Elucidate the Surface Charge Effects on the Acidic HER 44
2.5. Conclusion 50
2.6. Acknowledgements 50
Chapter 3. Heterogeneous Electron Transfer Reorganization Energy at the Inner Helmholtz Plane in a Polybromide Ionic Liquid 52
3.1. Abstract 54
3.2. Introduction 55
3.3. Experimental Methods 58
3.3.1. Materials 58
3.3.2. Synthesis of Polybromide Ionic Liquids 58
3.3.3. Electrochemical Measurements 59
3.3.4. Preparation of TiO2 Deposited Pt UME 60
3.3.5. Fit for CV data to the BV model 60
3.3.6. Electrochemical Impedance Spectroscopy 61
3.4. Results and Discussion 62
3.4.1. Ultrafast Mass Transport System of MEPBr2n+1 62
3.4.2. Verifications of Electron Transfer Kinetic Controlled Current 64
3.4.3. Application of the MHC Model to Electron Transfer Kinetics at Pt and Carbon Electrode 68
3.4.4. Effect of Electrode Surface Charge on the Reorganization Energy 72
3.5. Conclusion 76
3.6. Acknowledgements 77
3.7. Appendix: Derivation of the Current-Overpotential Equation for the simplified MHC Model 77
Chapter 4. Reorganization Energy in a Polybromide Ionic Liquid Measured by Scanning Electrochemical Cell Microscopy 80
4.1. Abstract 82
4.2. Introduction 83
4.3. Experimental Methods 86
4.3.1. Materials 86
4.3.2. Fabrication of Electrodes 86
4.3.3. Synthesis of MEPBr2n+1 Ionic Liquid 87
4.3.4. Electrochemical Measurements with SECCM 88
4.3.5. Fitting Methods to Obtain the Value of the Reorganization Energy from the CV Data 89
4.4. Results and Discussions 90
4.4.1. Electron Transfer Kinetics Controlled-voltammograms Measured by SECCM 90
4.4.2. Reorganization Energy at Polycrystalline Pt in MEPBr2n+1 94
4.4.3. Reorganization Energy for Br2 Reduction in MEPBr2n+1 Subject to the Elemental Composition of the Pt-Pd-Ru-Ir-Ag HEA 98
4.5. Conclusion 102
4.6. Acknowledgements 103
4.7. Appendix: Derivation of the current-overpotential equation for the MHC model 104
Chapter 5. Summary and Perspectives 105
5.1. Summary 105
5.2. Perspectives 107
Bibliography 108
๊ตญ๋ฌธ ์ด๋ก 122๋ฐ
์-์ฐํ๊ตฌ๋ฆฌ ์ฝ์ด-์ ๋๋ ธ ์์ด์ด ๋คํธ์ํฌ์ ๊ธฐ๋ฐํ ์ ์ฐยท์ ์ถ์ฑ ๋ฉค๋ฆฌ์คํฐ ์์์ ์ ์
ํ์๋
ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ณต๊ณผ๋ํ ๊ธฐ๊ณ๊ณตํ๋ถ, 2023. 2. ๊ณ ์นํ.Stretchable memristors are promising electrical components that can improve the mechanical robustness of neuromorphic devices. By the enhancement of mechanical robustness, they can be applied to wearable devices and soft robotics. Herein, a flexible and stretchable memristor based on nanowire networks is reported. The memristor mainly consists of Ag@Cu2O core-shell nanowires that are synthesized through a modified polyol process. The relative shell thickness was controlled in the synthesis process to achieve high stability and low energy consumption. The fabricated memristor shows memristive switching ratio over 104, with HRS resistance of ~100Mโฆ and LRS resistance of ~7kโฆ. It operated stably with retention time of 25000s and went through more than 200 switching cycles without significant resistance change. Furthermore, it well operated in harsh mechanical environments up to 9% strain and 30โ heating. The experimental results and the theoretical modelling of the core-shell NWs network based memristor was verified through simulation results, based on an implicit computational model.์ ์ถ์ฑ ๋ฉค๋ฆฌ์คํฐ๋ ๋ด๋ก๋ชจํฝ ๊ณตํ์ ์จ์ด๋ฌ๋ธ ์ ์๊ธฐ๊ธฐ์ ์ํํธ ๋ก๋ณดํฑ์ค์ ์ ๋ชฉ์ํฌ ์ ์๋๋ก ํ๋ ์ ๋งํ ์ ๊ธฐ ์์์ด๋ค. ๋ณธ ์ฐ๊ตฌ์์๋ ๋๋
ธ ์์ด์ด ๋คํธ์ํฌ์ ๊ธฐ๋ฐํ ์ ์ฐํ๊ณ ์ ์ถ์ฑ ์๋ ๋ฉค๋ฆฌ์คํฐ๋ฅผ ๊ฐ๋ฐํ์๋ค. ๋ฉค๋ฆฌ์คํฐ์ ์ฃผ์ ์ฌ๋ฃ์ธ ์-์ฐํ๊ตฌ๋ฆฌ ์ฝ์ด-์ ๋๋
ธ ์์ด์ด๋ ์ ํ ์ฐ๊ตฌ์ ํฉ์ฑ ๊ธฐ๋ฒ์ ๋ณํ ๋ฐ ๋ฐ์ ์์ผ ํฉ์ฑํ์๋ค. ๋ฉค๋ฆฌ์คํฐ์ ๋์ ์์ ์ฑ๊ณผ ๋ฎ์ ์๋์ง ์๋น๋์ ๋ฌ์ฑํ๊ธฐ ์ํด์๋ ์ฝ์ด-์ ๋๋
ธ ์์ด์ด์ ์๋์ ์ธ ์ ๋๊ป(RST)๋ฅผ ์ต์ ํํด์ผ ํ๋๋ฐ, ์ด๋ ํฉ์ฑ ๊ณผ์ ์์ ์ฑ๊ณต์ ์ผ๋ก ์ ์ด๋์๋ค. ์ต์ ํ ๊ณผ์ ์ ๊ฑฐ์ณ ์ ์๋ ๋ฉค๋ฆฌ์คํฐ๋ 104 ์ด์์ ๋์ HRS/LRS ์ ํญ ๋น์จ์ ๋ณด์ด๋ฉฐ, HRS ์ ํญ์ ~100Mฮฉ, LRS ์ ํญ์ ~7kฮฉ์ด์๋ค. 25000s์ ์๊ฐ๋์ ์์ ์ ์ผ๋ก ์๋ํ์์ผ๋ฉฐ, ํฐ ์ ํญ ๋ณํ ์์ด 200ํ ์ด์์ ์ค์์นญ ์ฌ์ดํด์ ๊ฑฐ์ณค๋ค. ๋ํ, ์ต๋ 9%์ ๋ณํ๊ณผ 30โ์ ๊ฐ์ด์ด ๊ฐํด์ง ๊ธฐ๊ณ์ ํ๊ฒฝ์์๋ ์ ์๋ํ์๋ค. ์ด๋ฌํ ์คํ ๊ฒฐ๊ณผ์ ์ด๋ก ์ ๋ชจ๋ธ๋ง์ ์๋ฎฌ๋ ์ด์
๊ฒฐ๊ณผ๋ฅผ ํตํด ๊ฒ์ฆํ์๋ค.Chapter 1. Introduction 3
1.1. Backgrounds and previous studies 3
1.2. Purpose of Research 4
Chapter 2. Materials and Method 6
2.1. Materials 6
2.2. Fabrication of AgNWs electrode 6
2.3. Synthesis of Ag@Cu2O Core-Shell NWs 7
2.4. Fabrication of Memristor 9
Chapter 3. Memristor Characterization 10
3.1. Operation Mechanism 10
3.2. Shell Thickness Optimization 13
3.3. Reliability Test 18
Chapter 4. Simulation 22
4.1. Single Junction Conductivity Modelling 22
4.2. Network Conductivity Modelling 24
Chapter 5. Conclusion 26
References 27
Abstract in Korean 29์
Analysis of the parameters affecting LiDAR intensity and its application in determining rock joint surface alteration
ํ์๋
ผ๋ฌธ (์์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์๋์ง์์คํ
๊ณตํ๋ถ, 2020. 8. ์ ์์.Rock mass characterization is required in many rock engineering projects. Among the parameters used to determine the rock mass rating (RMR), the discontinuity of rock mass, which includes the separation and weathering of the discontinuity surfaces, accounts for the largest share. In another method of classifying rock mass, the Geological Strength Index (GSI), the joint alteration factor (), which also indicates the discontinuity condition of rock mass such as the weathering of the discontinuity and the state of the filling, has a greater influence than any other parameters. There is a tendency lately for the classification of rock mass, which have previously been carried out in a variety of manual ways, to be automated due to the development of photogrammetry and light detection and ranging (LiDAR) technologies. For characterizing rockmass using LiDAR, qualities of rock discontinuities such as joint spacing, waviness, smoothness, and alteration should be determined. Estimating joint spacing, waviness, and smoothness factor by LiDAR have been studied using quantitative point cloud coordinates, but the task of estimating the joint alteration factor is more subjective. As previously mentioned, the effect of the joint alteration factor on the overall GSI is large. This study examines accurate approach for determining joint alteration factor from LiDAR intensity data, which is the return strength of the laser pulse that generated the point.
Previous studies have found that the reflective percentages or intensity of LiDAR are high for hard and less weathered rocks and small for more weathered and weak rocks. Therefore, through a number of laboratory experiments, a method of determining the joint alteration factor using LiDAR intensity was formulated by analyzing the factors directly affecting LiDAR. Factors that were not directly related to rock weathering were corrected. Laboratory experiments were performed to assess the impact of the scanning distance, incidence angle, roughness, micro-roughness, RGB color values, water saturation, and the mechanical properties of the rock on the LiDAR intensity and to ascertain how they affect it. As a result, it was concluded that the direct relationship between LiDAR intensity and the joint alteration factor could be obtained by correcting the scan distance, incidence angle, and RGB color values, which are the most influential factors to the LiDAR intensity when determining the joint alteration factor.
The separation of a discontinuity and the type of filling material also have a significant influence on the and on LiDAR intensity and this was what the laboratory experiment was also designed to measure. The separation was increased from 1 mm to 6 mm at 1 mm interval to measure the change in intensity. Bentonite and sand were used as a filling material to examine how they affected the intensity. As a result of the experiment, it was concluded that it was possible to estimate which and how much filling material existed through the degree of the change in the intensity in the separation or in the filling position.
A comparison of the hand-mapped data of rock alteration and the LiDAR intensity at three sites of rock slope also indicated a good relationship between intensity and joint alteration factor. The LiDAR intensity was high in the case of rock mass that was estimated to have a large GSI joint alteration factor or discontinuity condition within the RMR by means of hand mapping, and the degree to which this was the case was more apparent after correction on distance, incidence angle, and RGB value. Although correcting for each point would be the ideal, it would take significant time and effort. Consequently, for convenient and quick rock mass classification, the average value of the scanning distance, the incidence angle, or the RGB can be used alternatively.RMR์ ์ฐ์ ํ๊ธฐ ์ํด ์ฌ์ฉ๋๋ ์ฌ๋ฌ ์ธ์ ์ค ๋ถ์ฐ์๋ฉด์ ํ์, ํํ๋ ๋ฑ์ ํฌํจํ๋ ๋ถ์ฐ์๋ฉด ์ํ๋ ๊ฐ์ฅ ํฐ ๋น์ค์ ์ฐจ์งํ๋ค. ์๋ฐ ๋ถ๋ฅ๋ฅผ ์ํ ๋ ๋ค๋ฅธ ๋ฐฉ์์ธ GSI ์ฐ์ ์ ์์ด์๋ joint alteration factor, ์ฆ ๋ถ์ฐ์๋ฉด์ ํํ๋, ์ถฉ์ง๋ฌผ ์ํ ๋ฑ ๋ถ์ฐ์๋ฉด ์ํ ์ง์๋ joint condition factor๋ฅผ ์ต๋ 10๋ฐฐ ์ฆ๊ฐ์ํฌ ๋งํผ ๋ค๋ฅธ ์ด๋ค ์ง์๋ณด๋ค ๊ทธ ์ํฅ๋ ฅ์ด ํฌ๋ค. ๊ธฐ์กด ์๊ธฐ๋ก ๋ง์ด ์งํ๋๋ ์๋ฐ ๋ถ๋ฅ๊ฐ photogrammetry, LiDAR ๋ฑ์ ๊ธฐ์ ๋ฐ์ ์ผ๋ก ์๋ํ ๋๊ณ ์๋ ์ถ์ธ์ด๋ค. ๊ทธ ์ค LiDAR๋ฅผ ์ด์ฉํด ์๋ฐ ๋ถ๋ฅ๋ฅผ ํจ์ ์์ด joint spacing, waviness, smoothness ๋ฑ์ ์ ๋์ ์ธ ์ ๊ตฐ์ ์ขํ๋ฅผ ์ด์ฉํด ์ป๋ ์ฐ๊ตฌ๊ฐ ์ด๋ฃจ์ด์ง ๋ฐ ์์ผ๋ joint alteration factor๋ฅผ ์ฐ์ ํ๋ ์์
์ ๋ณด๋ค ์ฃผ๊ด์ ์ผ๋ก ์ฐ์ ์ ์ด๋ ค์์ด ์กด์ฌํ๋ค.
์์ ๋งํ๋ฏ์ด joint alteration factor๊ฐ ์ ์ฒด GSI์ ๋ฏธ์น๋ ์ํฅ์ ํฌ๋ฏ๋ก, ๋ฐ๋ผ์ LiDAR๋ฅผ ์ด์ฉํด ์ด๋ฅผ ๋ณด๋ค hand mapping์ ๊ฐ๊น์์ง๊ฒ ๊ตฌํ๋ ๋ฐฉ๋ฒ์ ๋ํด ์ฐ๊ตฌํ์๋ค. ๊ธฐ์กด ์ฐ๊ตฌ๋ค์ ํตํด LiDAR์ ๋ฐ์ฌ ๊ฐ๋๋ ๋จ๋จํ๊ณ ํํ๊ฐ ๋ ๋ ์๋ฐ์ ๋ํด์๋ ๊ทธ ๊ฐ์ด ํฌ๊ณ ๋ง์ด ํํ๋๊ณ ์ฝํด์ง ์๋ฐ์ ๋ํด์๋ ๊ทธ ๊ฐ์ด ์์์ ์ ์ ์์๋ค. ๋ฐ๋ผ์, ์ฌ๋ฌ ์ค๋ด ์คํ์ ํตํด LiDAR์ ์ง์ ์ ์ผ๋ก ์ํฅ์ ๋ฏธ์น๋ ์ธ์๋ฅผ ์ฐ์ ํ๊ณ ๊ทธ ์ค ์๋ฐ ํํ๋์๋ ์ง์ ์ ์ผ๋ก ๊ด๋ จ ์๋ ์ธ์๋ ๋ณด์ ํด LiDAR ๋ฐ์ฌ ๊ฐ๋๋ฅผ ์ด์ฉํด joint alteration factor๋ฅผ ๊ตฌํ๋ ๋ฐฉ๋ฒ์ ์ฐ๊ตฌํ๋ค. LiDAR intensity์ ์ง์ ์ ์ธ ์ํฅ์ ์ฃผ๋ ์ธ์๋ก ์ฃผ์ฌ ๊ฑฐ๋ฆฌ, ์
์ฌ๊ฐ, ๊ฑฐ์น ๊ธฐ, ์ฌํฌ๋ฅผ ์ด์ฉํ ๋ฏธ์ธ ๊ฑฐ์น ๊ธฐ, RGB ์์ ๊ฐ, ์์ ๊ธฐ๋ณธ ๋ฌผ์ฑ (UCS, ํ์ฑํ ์๋, ๊ณต๊ทน๋ฅ ), ์์์ ์ด๋ฃจ๋ ๊ด๋ฌผ ์กฐ์ฑ, ํฌํ๋๋ฅผ ์ ์ ํ๊ณ ์ผ๋ง๋ ์ํฅ์ ๋ฏธ์น๋์ง ๊ณ ์ฐฐํ๊ธฐ ์ํด ์ผ๋ จ์ ์ค๋ด ์คํ์ ์ํํ๋ค. LiDAR ๋ฐ์ฌ ๊ฐ๋์ ๊ฐ์ฅ ์ํฅ์ ๋ง์ด ๋ฏธ์น๋ ์์ธ๋ค์ธ ์ฃผ์ฌ ๊ฑฐ๋ฆฌ, ์
์ฌ๊ฐ, RGB ์์ ๊ฐ์ ๋ณด์ ํด ๋ฐ์ฌ ๊ฐ๋์ joint alteration factor์ ์ง์ ์ ์ธ ๊ด๊ณ๋ฅผ ์ฐ์ ํ๋ค.
ํ์ ๊ฐ๊ฒฉ, ์ถฉ์ง๋ฌผ์ ์ข
๋ฅ ์ญ์ ๋ฐ์ฌ ๊ฐ๋์ ๋ง์ ์ํฅ์ ๋ฏธ์น๋๋ฐ, ์ค๋ด์์ ํ์๋ฅผ 1 mm๋ถํฐ 6 mm๊น์ง 1 mm ๊ฐ๊ฒฉ์ผ๋ก ๋๋ ค๊ฐ๋ฉฐ ๋ฐ์ฌ ๊ฐ๋์ ๋ณํ๋ฅผ ์ธก์ ํ๊ณ ์ถฉ์ง๋ฌผ๋ก bentonite, sand๋ฅผ ์ฌ์ฉํด ๊ฐ๊ฐ intensity์ ์ด๋ค ์ํฅ์ ๋ฏธ์น๋์ง ์ดํด๋ณด์๋ค. ์คํ ๊ฒฐ๊ณผ ํ์๋ ์ถฉ์ง๋ฌผ ๊ตฌ๊ฐ์์ ๋ฐ์ฌ ๊ฐ๋๊ฐ ๋ณํ๋ ์ ๋๋ฅผ ํตํด ์ด๋ค ์ถฉ์ง๋ฌผ์ด ์ด์ฉ๋์๋์ง ์ถ์ธกํ ์ ์๋ค๋ ๊ฒฐ๋ก ์ ๋ด๋ ธ๋ค.
๋ถ์ฐ์๋ฉด์ ๋ณ์ง๋๊ฐ ๋ค๋ฅธ ์ธ ์๋ฐ ์ฌ๋ฉด์ LiDAR๋ก ์ค์บํ๊ณ ๊ทธ ๋ฐ์ฌ ๊ฐ๋๋ฅผ ์ป์ด ์์ ์ธ๊ธํ ์ธ์๋ค์ ๋ณด์ ํ๋ค. ๊ทธ ๊ฒฐ๊ณผ๋ฅผ hand mapping์ ํตํด ์ป์ ๋ถ์ฐ์๋ฉด ๋ณ์ง๋์ ๋น๊ตํด๋ณธ ๊ฒฐ๊ณผ ๋ฐ์ฌ ๊ฐ๋๋ ๋ถ์ฐ์๋ฉด ๋ณ์ง๋๋ฅผ ๋ฒ์๋ก ์ฐ์ ํ๊ธฐ์ ์ถฉ๋ถํ๋ค.Chapter 1. Introduction ................................................................. 1
1.1 Background .................................................................................. 1
1.2 Previous researches........................................................................ 2
1.2.1 GSI system for rock mass classification...........................................2
1.2.2 Relationship between the degree of weathering and LiDAR intensity ...........................................................................................................................7
1.3 Objectives .................................................................................. 10
Chapter 2. LiDAR Technology ...................................................... 11
2.1 Characteristics of LiDAR.............................................................. 11
2.2 LiDAR Intensity ......................................................................... 18
Chapter 3. Experimental work ..................................................... 21
3.1 Method Overview ........................................................................ 21
3.2 Laboratory experiments ................................................................ 21
3.2.1 Specimens used ..............................................................................21
3.2.2 Specification of the LiDAR used ...................................................29
Chapter 4. Results and Discussion................................................. 33
4.1 Relationship between LiDAR intensity and related variables ............... 33
4.1.1 Distance..........................................................................................33
4.1.2 Incidence angle...............................................................................35
4.1.3 JRC.................................................................................................37
4.1.4 Micro-roughness ............................................................................38
4.1.5 Degree of saturation .......................................................................40
4.1.6 Mechanical and physical properties ...............................................41
4.1.7 Mineral composition ......................................................................45
4.1.8 RGB value......................................................................................49
4.1.9 Separation.......................................................................................53
4.1.10 Filling material .............................................................................56
4.1.11 Summary ......................................................................................63
4.2 Application of LiDAR intensity to determination of the joint alteration factor determination .......................................................................... 65
4.2.1 GSI joint alteration factor...............................................................65
4.2.2 Field applications ...........................................................................65
Chapter 5. Conclusions ................................................................ 80
Reference ................................................................................... 83
Appendix A. LiDAR intensity of point clouds in each site before and after correction .................................................................................. 87
์ด ๋ก .................................................................................... 90Maste
A Robust Stochastic Optimization Model for Petroleum Logistic Network
๋ค์์ ์์ ์ ์ ํญ์ผ๋ก๋ถํฐ ์ฌ๋ฌ ์ ์ ๊ณต์ฅ์ผ๋ก ์์ก๋ ์์ ๋ฅผ ์ ์ ํ์ฌ ์์ฐํ ์ ํ์ ๋ฅผ ๊ธ๋ก๋ฒ ์์์์ฅ์ผ๋ก ๋ฐฐ๋ถํ๋ ์์ ๋ฌผ๋ฅ๋คํธ์ํฌ์ ์ต์ ํ๋ ๊ธ๋ก๋ฒ ์์ ๋ฉ์ด์ ์ ์ค์ํ ์์ฌ๊ฒฐ์ ๋ฌธ์ ์ด๋ค. ์ด ๋
ผ๋ฌธ์ ์ ํ์ ์์ฅ์ ๊ฐ๊ฒฉ, ์์ก๋น ๋ฐ ์์ ๋ณ๋์ ์ํฅ์ ๋ฐ์ํ์ฌ ์์ ์์ก, ์ ์ ๋ฐ ์ ํ์ ๋ฐฐ๋ถ์ ์ต์ ํํ๊ธฐ ์ํ ์์ ๋ฌผ๋ฅ๋คํธ์ํฌ์ ๋ก๋ฒ์คํธ ์ถ๊ณ์ ๋ชจํ์ ์ ์ํ๋ค. ๊ณ์ฐ์คํ์ ์ ํ์ ์์ฅ์ ๊ฐ๊ฒฉ, ์์ก๋น ๋ฐ ์์ ๋ณ๋์ ๊ดํ ์๋๋ฆฌ์ค ๊ธฐ๋ฐ์ ๋ฐ์ดํฐ๋ฅผ ์ฌ์ฉํ์ฌ ์ต์ ํ ๋ชจํ์ ์ ์ฉํ์์ผ๋ฉฐ, ๊ทธ ๊ฒฐ๊ณผ๋ฅผ ๋ฐํ์ผ๋ก ์ ์ํ ์ต์ ํ ๋ชจํ์ ์ ์ฉ์ฑ๊ณผ ํ๋น์ฑ์ ๊ฒ์ฆํ์ฌ ๋ณด๊ณ ํ์๋ค. |It is important for major oil companies to make decisions about the optimization of two-stage petroleum logistic networks which transport crude oil from loading sources to various other refineries and distribute them to the global market to satisfy demand. In this paper, a robust stochastic model of the petroleum logistics network is presented for optimized transportation refining distribution reflecting the effects of price, cost and demand fluctuations in the product market. Calculation experiments were applied to the optimization model using scenario-based data on price, cost and demand fluctuations in the product market. Based on the results, the validity of the proposed optimization model is verified and reported.1. ์๋ก 1
2. ์์ ๋ฌผ๋ฅ๋คํธ์ํฌ ๋ฌธ์
2.1 ์ ์ ์ฐ์
์ ์ดํด 3
2.2 ์์ ๋ฌผ๋ฅ๋คํธ์ํฌ 7
2.3 ์ ํ์ฐ๊ตฌ 9
3. ๋ฌธ์ ์ ์ ์ํ
3.1 ํ์ ์ ๋ชจํ์ ์ ์ํ 10
3.2 2๋จ๊ณ ์ถ๊ณ์ ๋ชจํ์ ์ ์ํ 12
3.3 ๋ก๋ฒ์คํธ ์ต์ ํ ๋ชจํ 16
3.3.1 RO ๋ชจํ 16
3.3.2 RR ๋ชจํ 20
4. ๊ณ์ฐ์คํ ๋ฐ ๊ฒฐ๊ณผ ๊ฒํ
4.1 ์๋ฃ ์ค๋น 22
4.2 ๊ณ์ฐ์คํ 23
4.2.1 ํ์ ์ ๋ชจํ 23
4.2.2 2๋จ๊ณ ์ถ๊ณ์ ๋ชจํ 34
4.2.3 ๋ก๋ฒ์คํธ ์ต์ ํ ๋ชจํ 41
4.3 ์คํ๊ฒฐ๊ณผ ๊ฒํ 53
4.3.1 ๋ฏผ๊ฐ๋ ๋ถ์ 53
4.3.2 ์์ ์ ๋ณด์ ๊ธฐ๋๊ฐ์น 58
4.3.3 ์ถ๊ณ์ ํด์ ๊ธฐ๋๊ฐ์น 59
4.3.4 ์ ์ ๋ง์ง์ ๋น๊ต 61
4.3.5 ๋ก๋ฒ์คํธ ์ต์ ํ ๋ชจํ์ ์ ํจ์ฑ 62
5. ๊ฒฐ๋ก 64
์ฐธ๊ณ ๋ฌธํ 66Maste
๋ฏธ๊ตญ ๋ฐ ์ ๋ฝ์ฐํฉ์ ๅฐ์ธ๋ ์๊ณ๊ด์ธ ์ฌ๋ก์ฐ๊ตฌ ๋ฐ ํฅํ ํ๊ตญ์ ์๊ณ๊ด์ธ ํ์ฉ ๊ด๋ จ ์์ฌ์
ํ์๋
ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ตญ์ ๋ํ์ ๊ตญ์ ํ๊ณผ(๊ตญ์ ํต์์ ๊ณต), 2021.8. ์๋๊ทผ.Countervailing duty or anti-subsidy measure had been mostly utilized by countries with power such as the United States and the European Union in the past. Today, however, many emerging countries, especially India, are increasingly utilizing it as their trade remedy measure more and more while Korea has never utilized it before in its history. As India has never been an easy trading partner to many countries, especially for Korea, such recent change in India cannot be welcomed to the rest of the world.
In 2019, India initiated its first anti-subsidy investigation on Korea concerning imports of Styrene Butadiene Rubber originating in Korea which was recently decided by the Central Government of India not to impose countervailing measures as of March 2021. Korean products have been subject to the second most numerous anti-dumping investigations by India, that is after China. Given that Korea is merely the 8th largest trading partner of India accounting for three percent of its total trade volume, whereas China is Indiaโs major trading country accounting for 14% of its entire trade volume, India has been particularly harsh on Korean products. Despite the effort of two countries to have free and harmonized trade by signing Korea-India CEPA, Indiaโs frequent application of trade remedy measures against products originating in Korea have brought difficulties for many Korean exporters to expand their market into India.
Today India is already the fifth country for filing the most CVD measures in the world, which is growing at a rapid rate, despite the fact that it had its first final finding in 2016. Until several years ago, India used to be only a victim of frequent CVD measures taken by other countries, mainly United Sates, and the European Union, the two of their main trading partners.
The United States currently imposes the most CVD measures on Indian imports, which is tallied up to 26 CVD measures as of July 2021. As a single country, the US is the largest goods export market for India accounting for about 16% share. Recently, the U.S. government has taken off India from the preferential list, which puts India in a vulnerable position for the future incoming AD and CVD measures against India. As for the European Union, it is the largest trading partner for India. The EU has four ongoing CVD measure upon Indian products. It has initiated its first CVD investigations against India in 1997 and has continued its imposition.
This paper looked into the ongoing CVD cases initiated by the US and the EU against Indian products that have been found to be countervailable, and will answer the following questions: What are the CVD cases that have been investigated on products originating in India by the U.S. and the EU that are found to be countervailable? Are there any product lines or industry in India that are frequently accused of CVD measures? How had Indian government dealt with the CVD measures imposed on the country? What are the commonly used export incentives granted by the Indian government? What can be the implications for Korea based on the analysis of CVD cases by the EU and the US? How much is Korea importing the Indian products that have been accused of being countervailable by the US or/and the EU? Will it be possible that Korea is also being injured from its imports of the very same products from India? What can these findings imply to Koreaโs potential CVD utilization? Answering these questions will not only facilitate the understanding of Indiaโs subsidy schemes that have been frequently accused of CVD measures, but also throw lights on Koreaโs potential CVD measure utilization.๊ตญ๋ฌธ ์ด๋ก
์๊ณ๊ด์ธ ๋๋ ๋ฐ๋ณด์กฐ๊ธ ์ ์ฑ
์ ๊ทธ๊ฐ ๋ฏธ๊ตญ๊ณผ ์ ๋ฝ์ฐํฉ๊ณผ ๊ฐ์ ๊ฐ๋๊ตญ์ ์ํด ์ฃผ๋ก ํ์ฉ๋์ด์๋ค. ํ์ง๋ง ์ค๋๋ ์ ํนํ ์ธ๋์ ๊ฐ์ ๋ง์ ์ ํฅ ๊ตญ๊ฐ๋ค ๋ํ ์๊ณ๊ด์ธ ์ ์ฑ
์ ํ์ฉํ๋ ๊ฒ์ด ์ฆ๊ฐํ๋ ์ถ์ธ์ ์๋ค. ๊ทธ์ ๋ฐ๋ฉด์ ์ฐ๋ฆฌ๋๋ผ๋ ์ญ์ฌ์ ์๊ณ๊ด์ธ์กฐ์น๋ฅผ ์ทจํด๋ณธ ์ ์ด ์๋ค. ์ธ๋๊ฐ ๊ทธ๊ฐ ํนํ ํ๊ตญ์ ํฌํจํ ๋ง์ ๋๋ผ๋ค์๊ฒ ์์ด์ ์ฌ์ด ๋ฌด์ญ ํํธ๋์๋ ์ ์ด ์๋ ๋งํผ, ์ต๊ทผ ์ด๋ฌํ ๋ณํ๋ ๋จ์ฐ ์ข์ ๋ด์ค๋ ์๋๋ค.
2019๋
, ์ธ๋๊ฐ ์ฐ๋ฆฌ๋๋ผ์ ์คํ์ด๋ ๋ทฐํ๋ค์ด์๊ณ ๋ฌด(Styrene Butadiene Rubber)์ ๋ํ์ฌ ์๊ณ๊ด์ธ ์กฐ์ฌ๋ฅผ ๊ฐ์ํ์๋ค. 2021๋
3์, ์ธ๋ ์ ๋ถ๊ฐ ํด๋น ์กฐ์ฌ๋ฅผ ์ฒ ํํ์์ง๋ง, ๊ทธ๊ฐ ์ฐ๋ฆฌ๋๋ผ์๊ฒ ๋ฐ๋คํ ์กฐ์น๋ง์ ๋ถ๊ณผํด์๋ ์ธ๋๊ฐ ํ๊ตญ์ ์๋๋ก ์ฒซ ์๊ณ๊ด์ธ ์กฐ์ฌ ๊ฐ์๋ฅผ ํ์๋ค๋ ๊ฒ์ ๋์ฌ๊ฒจ๋ณผ ๋งํ๋ค. ํ๊ตญ์ ์ธ๋๊ฐ ์ค๊ตญ ๋ค์์ผ๋ก ๋ง์ ๋ฐ๋คํ๊ด์ธ๋ฅผ ๋ถ๊ณผํ๋ ๋๋ผ๋ค. ํ๊ตญ์ ์ ์ฒด ๋ฌด์ญ๋์ 3%๋ฅผ ์ฐจ์งํ๋ ์ธ๋์ 8๋ฒ์งธ ๋ฌด์ญ ์๋๊ตญ์ด๊ณ , ์ค๊ตญ์ ์ ์ฒด ๋ฌด์ญ๋์ 14%๋ฅผ ์ฐจ์งํ๋ ๊ฐ์ฅ ํฐ ๋ฌด์ญ์๋๊ตญ์ธ ๊ฒ์ ๊ฐ์ํ ๋, ์ธ๋๊ฐ ํ๊ตญ ์ํ์ ํนํ ์ ๋์ ์ธ ์ธก๋ฉด์ด ๊ฐํ๋ค๋ ๊ฒ์ ๋ถ์ธํ ์ ์๋ค. ์์ ๋กญ๊ณ ์กฐํ๋ก์ด ๋ฌด์ญ ๊ต๋ฅ๋ฅผ ์ํ ๋
ธ๋ ฅ์ ์ผ๋ถ์ธ ํยท์ธ CEPA ์ฒด๊ฒฐ์๋ ๋ถ๊ตฌํ๊ณ ์ธ๋์ ์ฆ์ ๋ฌด์ญ๊ตฌ์ ์กฐ์น๋ ํ๊ตญ ์์ถ์
์๋ค์ด ์ธ๋ ์์ฅ์ ์ง์ถํ๋ ๋ฐ์ ์์ด ๋ง์ ์ด๋ ค์์ ์๊ฒจ์๋ค.
์ธ๋๋ 2016๋
๋ ์ฒซ ์๊ณ๊ด์ธ ํ์ ์กฐ์น ์ดํ, ์ค๋๋ ์ด๋ฏธ ์ธ๊ณ์์ ๋ค์ฏ๋ฒ ์งธ๋ก ๊ฐ์ฅ ๋ง์ ์๊ณ๊ด์ธ ์กฐ์น๋ฅผ ๋ถ๊ณผํ๋ ๊ตญ๊ฐ๋ก ๊ธ๋ถ์ํ๋ค. ๋ช ๋
์ ๋งํด๋ ์ธ๋๋ ํ๊ตญ๊ณผ ๋ง์ฐฌ๊ฐ์ง๋ก ๋ฏธ๊ตญ, ์ ๋ฝ ์ฐํฉ ๋ฑ ์ฃผ๋ก ๋ค๋ฅธ ๊ฐ๋๊ตญ๋ค์ ์ํด ์ฆ์ ์๊ณ๊ด์ธ๋ฅผ ๋ถ๊ณผ๋ฐ๊ธฐ๋ง ํ๋ ๊ตญ๊ฐ ์ค ํ๋์๊ณ ์ด๋ค์ ์ธ๋์ ์ฃผ์ ๋ฌด์ญ ์๋๊ตญ์ด๋ค.
๋ฏธ๊ตญ์ 2021๋
7์ ๊ธฐ์ค, ์ธ๋๋ฅผ ๋์์ผ๋ก 26๊ฐ์ ์๊ณ๊ด์ธ ์กฐ์น๋ฅผ ์ํ์ค์ผ๋ก ์ด๋ ๊ฐ์ฅ ๋ง์ ์ซ์๋ค. ๋จ์ผ๊ตญ์ผ๋ก๋ ๋ฏธ๊ตญ์ด ์ธ๋์ ๊ฐ์ฅ ํฐ ์์ถ ์์ฅ์ผ๋ก, ์ ์ฒด ๋ฌด์ญ๊ท๋ชจ์ 16%๋ฅผ ์ฐจ์งํ๋ค. ์ต๊ทผ ๋ฏธ๊ตญ์ ์ธ๋๋ฅผ ์ฐ๋๋ชฉ๋ก(preferential list)์์ ์ ์ธํ๋ฉฐ ํฅํ ์ธ๋๋ฅผ ํฅํ ์๊ณ๊ด์ธ ๋ฐ ๋ฐ๋คํ ์กฐ์น๋ฅผ ๋ ์์ํ๊ฒ ํ๋ฐ์๋ค. ์ ๋ฝ์ฐํฉ์ ์ธ๋์ ๊ฐ์ฅ ํฐ ๋ฌด์ญ์๋๊ตญ์ผ๋ก, ํ์ฌ ์ธ๋์๊ฒ 4๊ฐ์ ์๊ณ๊ด์ธ ์กฐ์น๋ฅผ ์ทจํ๊ณ ์๋ค. ์ ๋ฝ์ฐํฉ์ 1997๋
์ธ๋๋ฅผ ์๋๋ก ์ฒซ ๋ฒ์งธ ์๊ณ๊ด์ธ ์กฐ์น ์ดํ ์ง๊ธ๊น์ง ๊พธ์คํ ์กฐ์น๋ฅผ ์ทจํ๊ณ ์๋ค.
๋ณธ ์ฐ๊ตฌ๋ ๋ฏธ๊ตญ๊ณผ ์ ๋ฝ์ฐํฉ์ด ์ธ๋๋ฅผ ์๋๋ก ์กฐ์น์ค์ธ ์๊ณ๊ด์ธ ์ฌ๋ก๋ค์ ๋ณด์กฐ๊ธ ์ค์ฌ์ผ๋ก ๋ถ์ํ๋ค. ๊ฐ ๊ตญ์ ์ฃผ์ฅ์ ํตํฉํ์ฌ ๋ณต์์ ์ฌ๋ก์์ ๋ฐ๋ณต์ ์ผ๋ก ๋ฑ์ฅํ๋ ์ฃผ์ฅ ๋ฐ ๊ทผ๊ฑฐ๋ค์ ์ดํด๋ณธ๋ค. ๋ํ ๋ณธ ์ฐ๊ตฌ๋ ์ฐ๊ตฌ ๋์์ ์ธ๋์ํ๋ค์ ๋ํ์ฌ ํ๊ตญ๊ณผ์ ๋ฌด์ญ ํ๋ฆ์ ํ์
ํ๊ณ , ํด๋น ํ๋ชฉ์ ๋ํ ํ๊ตญ์ ์ธ๋์ ๋ํ ๋ฌด์ญ์์กด๋๋ฅผ ์ดํ๋ค. ์ฐ๊ตฌ ๊ฒฐ๊ณผ ์ฐ๊ตฌ ๋์ 8๊ฐ์ํ ๋ชจ๋ ํ๊ตญ์ด ์์
๊ตญ ์ธก์ด๋ฉฐ, ์ด ์ค์์๋ ํ๊ตญ์ Carbazole Violet Pigment 23, Polyester Textured Yarn, ๊ทธ๋ฆฌ๊ณ Graphite Electrode systems์์ ์ ๋
๋ง์ ์์
๋์ ๋ณด์๋๋ฐ ์ฒซ ๋ ํ๋ชฉ์ ๊ฒฝ์ฐ ๋ฏธ๊ตญ์ด ๋ฐ๋คํ ๋ฐ ์๊ณ๊ด์ธ ๋ชจ๋ ๋ถ๊ณผ์ค์ด๋ฉฐ, ๋ง์ง๋ง ํ๋ชฉ์ ๊ฒฝ์ฐ์๋ ์ ๋ฝ์ฐํฉ์ด 2004๋
๋ถํฐ ๊พธ์คํ ๋ฐ๋คํ ๋ฐ ์๊ณ๊ด์ธ ๋ชจ๋ ๋ถ๊ณผํด์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ์ด์ ๊ฐ์ ์ฐ๊ตฌ ๊ฒฐ๊ณผ๋ค์ ๋ฐํ์ผ๋ก ํ๊ตญ์ ์ ์ฌ์ ์๊ณ๊ด์ธ ํ์ฉ์ ์ด๊ตฌํ๋ค.I. INTRODUCTION 10
1.1. Background and Significance of the Study 10
1.2. Purpose of the Study 11
II. INDIA'S TRADE OVERVIEW 13
2.1. India's Trade Status quo 13
2.2. Overview of India's trade policy 17
III. CASE STUDY THE UNITED STATES 23
3.1. Background: Trade Relations with India 23
3.2. US's CVD measures status quo 25
3.3. US's CVD measures in force towards India 27
3.3.1. Carbazole Violet Pigment 23 29
3.3.2. Polyester Textured Yarn 39
3.3.3. Quartz Surface Products 48
3.3.4. Stainless Steel Flanges 55
IV. CASE STUDY EUROPEAN UNION 60
4.1. Background: Trade Relations with India 60
4.2. EU's CVD measures status quo 62
4.3. EU's CVD measures in force towards India 64
4.3.1. Stainless steel bars and rods 66
4.3.2. PET 71
4.3.3. Tubes and pipes of ductile cast iron 75
4.3.4. Graphite Electrode systems 80
V. CASE STUDY REVIEW 85
5.1. Overall Case Study Review 85
5.2. The US-India CVD case reviews in relation to Korea 88
5.2.1. US-India CVD cases overview 88
5.2.2 Carbazole Violet Pigment(CVP) 23 90
5.2.3. Polyester Textured Yarn 92
5.2.4. Quartz Surface Products 95
5.2.5. Stainless Steel Flanges 98
5.3. The EU-India CVD cases reviews in relation to Korea 100
5.3.1. EU-India CVD cases Overview 100
5.3.2. Stainless steel bars and rods 101
5.3.3. PET 104
5.3.4. Tubes and pipes of ductile cast iron 105
5.3.5. Graphite Electrode systems 106
VI. KOREA's CVD UTILIZATION 108
6.1. Korea's Trade Remedy Measure Overview Focus on CVD Measures 108
6.2. Implications for Korea's Potential CVD Utilization 111
VII. CONCLUSION 113
APPENDIX 115
REFERENCES 120
๊ตญ๋ฌธ์ด๋ก 122์
๋ค๊ณต์ฑ ๋งค์ง ํ๋ฆ์ฅ์์์ ๋ฐ์ด์คํ๋ฆ ๋ฉ์นด๋์ฆ์ ๊ดํ ์์น ๋ชจ๋ธ๋ง
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