以響應曲面法進行自加熱真空薄膜蒸餾的最佳化｜國立臺灣科技大學博碩士論文系統

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研究生：	Shaneza Fatma Rahmadhanty Shaneza Fatma Rahmadhanty
論文名稱：	以響應曲面法進行自加熱真空薄膜蒸餾的最佳化 Optimization of Self-heated Vacuum Membrane Distillation using Response Surface Methodology
指導教授：	林柏廷 Po-Ting Lin
口試委員:	洪維松 Wei-Song Hung 張敬源 Ching-Yuan Chang
學位類別：	碩士 Master
系所名稱：	工程學院 - 機械工程系 Department of Mechanical Engineering
論文出版年：	2022
畢業學年度：	110
語文別：	英文
論文頁數：	162
外文關鍵詞：	Vacuum Membrane Distillation
相關次數：	點閱：315 下載：1
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Currently, technology is increasingly advanced and has penetrated into several fields such as Membrane Distillation (MD) in water treatment, especially to purify saline water, in the face of the increasing scarcity of clean water needed for consumption, both in the domestic, agriculture, and industrial sectors. One of the configurations in MD systems, Vacuum Membrane Distillation (VMD) system, which employs a Graphene-PVDF membrane heated by power supply, in this case using DC power with low voltage, to eliminate feed pre-feed heating and temperature polarization, is interesting to learn. In addition, to enhance the performances, such as maximizing Water Permeate Flux (JW), Temperature Polarization Factor (TPF), Gain Output Ratio (GOR), and minimizing Specific Heating Energy (QSH), several different designs are made and compared. In this research, four parameters are selected: DC power supply’s voltage, feed flow rate, the length, and the width of the cell body's slot. Ansys FLUENT software is utilized to simulate the system, followed by Minitab software to analyze the results using Response Surface Method (RSM) which aims to achieve the optimal design parameters and to discover the effect of the design parameters. The results show that horizontal shape gives better performances than the vertical one, voltage is the most significant factor to all the performances, and specifically for JW and TPF are also affected by flow rate afterwards as response with 5% significance level. While the best performance obtained from RSM is the 5-slot in horizontal shape, which can be proven by experimental validation with the factors of 2 mm for the slot’s width, 20 mm for the slot’s length, 12.2222 V for the DC voltage, and 5 mL/min for the feed flow rate. And the performance’s responses are 2.2860 L/m2h for JW, 102.58% for TPF, 0.2487 kWh/L for QSH, and 2.6882 for GOR. Moreover, the effective heating temperature for 5-slot in horizontal design is also analyzed through this study and it is found to be 39°C.

ABSTRACT i
TABLE OF CONTENTS ii
NOMENCLATURE v
ABBREVIATIONS vii
LIST OF TABLES viii
LIST OF FIGURES ix
CHAPTER 1. INTRODUCTION    1
1. Introduction to Optimization in Self-heated Vacuum Membrane Distillation System 1
2. Research Development of Optimization in Membrane Distillation 3
2.1. Literature Reviews 33
2.2. Summary 4
3. Scope of the Present Study 5
CHAPTER 2. THEORETICAL BACKGROUND 6
1. Self-heated Vacuum Membrane Distillation System 6
1.1. Introduction to Membrane Distillation 6
1.2. Introduction to Self-heated Vacuum Membrane Distillation System 8
1.3. The Performance of Self-heated Vacuum Membrane Distillation System 9
2. Response Surface Methodology 12
2.1. Introduction to Response Surface Methodology 12
2.2. Types of Models in Response Surface Methodology 13
2.3. Optimization in Response Surface Methodology 14
2.4. Design of Experiments in Response Surface Methodology 16
2.5. The Advantages of Response Surface Methodology 19
CHAPTER 3. METHODOLOGY 20
1. Flow Chart of Methodology 20
2. Selection of Variables 21
3. Design of Experiment 22
4. Simulation 24
5. Numerical Analysis 25
6. RSM Creation 25
7. RSM Optimization 27
8. Experiment Validation 27
CHAPTER 4. RESULTS AND DISCUSSION 30
1. Original Design Case 30
1.1. Results Data 30
1.2. Analyze Response Surface Design 30
1.3. Response Optimizer 33
2. 1-Slot in Vertical Shape Design Case 35
2.1. Results Data 35
2.2. Analyze Response Surface Design 35
2.3. Response Optimizer 40
3. 1-Slot in Horizontal Shape Design Case 42
3.1. Results Data 42
3.2. Analyze Response Surface Design 42
3.3. Response Optimizer 47
4. 2-Slot in Vertical Shape Design Case 49
4.1. Results Data 49
4.2. Analyze Response Surface Design 49
4.3. Response Optimizer 54
5. 2-Slot in Horizontal Shape Design Case 56
5.1. Results Data 56
5.2. Analyze Response Surface Design 56
5.3. Response Optimizer 61
6. 3-Slot in Vertical Shape Design Case 63
6.1. Results Data 63
6.2. Analyze Response Surface Design 63
6.3. Response Optimizer 68
7. 3-Slot in Horizontal Shape Design Case 70
7.1. Results Data 70
7.2. Analyze Response Surface Design 70
7.3. Response Optimizer 75
8. 4-Slot in Vertical Shape Design Case 77
8.1. Results Data 77
8.2. Analyze Response Surface Design 77
8.3. Response Optimizer 82
9. 4-Slot in Horizontal Shape Design Case 84
9.1. Results Data 84
9.2. Analyze Response Surface Design 84
9.3. Response Optimizer 88
10. 5-Slot in Vertical Shape Design Case 89
10.1. Results Data 89
10.2. Analyze Response Surface Design of 5-Slot in Vertical Shape Design Case 90
10.3. Response Optimizer 95
11. 5-Slot in Horizontal Shape Design Case 97
11.1. Results Data 97
11.2. Analyze Response Surface Design 97
11.3. Response Optimizer of 5-Slot in Horizontal Shape Design Case 101
12. 6-Slot in Vertical Shape Design Case 102
12.1. Results Data 102
12.2. Analyze Response Surface Design 103
12.3. Response Optimizer 108
13. The Comparison of The Optimal Results in Each Case 110
14. Experimental Validation 111
15. Effective Heating Temperature 113
CHAPTER 5. CONCLUSION 115
REFERENCES 116
APPENDIX 119
Appendix 1. The Geometry Design Sample of Each Design Case 119
Appendix 2. Boundary Conditions’ Zones in Simulation 128
Appendix 3. RSM Creation and Optimization Steps using Minitab 129
Appendix 4. ANOVA Table of Each Design Case. 133
Appendix 5. Effective Heating Area’s Percentage of Each Critical Temperature Table 145
CURRICULUM VITAE 147


                                

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