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목차

제1장 서론 27

제1절 연구필요성 및 목표 28

1. 연구개발의 필요성 28

2. 연구개발의 목표 31

3. 연구개발의 추진방법 및 연도별 추진 체계 32

제2장 국내외 기술 개발 현황 34

제1절 국내 정책 동향 35

1. 미국 지표수처리규정(SWTR) 및 관련규정 개괄 35

2. 국내 소독공정 정수처리기준 강화 43

3. 정수처리기준 강화에 대한 대응방안 47

제2절 국외 연구 동향 48

1. 복합소독 적용 기술의 종류 및 특성 48

2. 복합소독 기술 연구 동향 53

제3절 국내외 지적재산권 동향 55

1. 기술 특허 분석 범위 및 분석 기준 56

2. 정수처리 설비에 적용 가능한 복합소독 기술 분야의 동향 62

3. 포트폴리오로 본 정수처리 설비에 적용 가능한 복합소독 기술 개발 분야의 위치 65

4. 국가별 특허 동향 및 점유율 69

제4절 국내외 소독기술 동향 81

1. 복합소독기술 도입사례 81

2. 국내 소독기술 현황 및 특성 87

제3장 연구개발 결과 및 활용계획 99

제1절 복합소독기술 개발 방향 및 실용화 100

1. 복합소독 정의 및 대상공정 선정 100

2. 복합소독 자동화장치 개발 방향 101

3. 고도산화공정의 복합소독공정에의 적용 104

4. 미생물의 불활성화 메커니즘 규명 123

5. 복합소독 반응기 해석 138

제2절 통합소독모델 및 반응해석 143

1. 통합소독모델 143

2. 통합소독모델 적용 절차 149

3. 반응조 유동해석 모델 153

4. 미생물 제거 모델 170

5. 소독부산물 예측 모델 174

제3절 오존공정 설계, 운영 및 최적화 179

1. 오존공정의 설계 및 운영 최적화에 대한 개요 179

2. 오존공정 설계 최적화 209

3. 오존공정 운영 최적화 229

4. 오존공정 평가 프로그램 개발 245

제4절 복합소독공정 설계 및 운전 최적화 246

1. 복합소독공정 소독제 주입 및 접촉설비 구성방안 246

2. 복합소독공정 반응기 해석을 위한 LIF 기술 개발 256

3. 복합소독 접촉지 유동 해석 기술 266

4. 복합소독 소독부산물 평가 및 예측 모델 개발 279

5. 복합소독 자동화설비 모델 및 제어 알고리즘 개발 316

6. 사용자지향의 복합소독공정 소프트웨어 개발 321

7. 복합소독 접촉설비 설계 최적화 335

제5절 복합소독 자동제어 기술 341

1. 복합소독 실증플랜트 구성 및 운전 341

2. 복합소독 자동제어 시스템 알고리즘 343

3. 무선 모바일 기반의 복합소독 통합 평가 프로그램 346

제6절 요약 350

제4장 결론 352

제1절 연구개발 목표의 달성도 353

제2절 관련분야 기술발전 기여도 358

제3절 연구개발결과의 활용계획 359

제5장 참고문헌 365

Table 1.1.1.1. Required CT or IT Value for 2 log(99 %) Inactivation(pH 7.1, 20 ℃, Phosphate Buffer Condition) 30

Table 2.1.1.1. Comparison of SWTR, IESWTR and LT1ESWTR 38

Table 2.1.1.2. Rules and Target Microorganisms of Water Treatment (USA) 39

Table 2.1.1.3. Rules of Microorganisms and DBPs 40

Table 2.1.1.4. Level of Treatment Required for Filtered Systems 41

Table 2.1.1.5. Cryptosporidium Treatment Requirements for Unfiltered Systems 43

Table 2.1.2.1. Rules of Turbidity for Filtered Systems 45

Table 2.1.2.2. Removal of Virus and Giardia Cyst by Filtration 45

Table 2.1 2.3. Factors for Inactivation Calculation 46

Table 2.1.2.4. Required Virus and Giardia Inactivation for Water Treatment Systems 46

Table 2.2.1.1. Disinfectant/Oxidant Characteristics 50

Table 2.2.1.2. Formation of DBPs 51

Table 2.2.1.3. Application of Sequential Disinfection Process 51

Table 2.2.2.1. Results of References about Sequential Disinfection 54

Table 2.3.1.1. Analysis Criteria of Patent 56

Table 2.3.1.2. Criteria of Technology 57

Table 2.3.1.3. Keyword of Classification 58

Table 2.3.1.4. Index of Patent Analysis 62

Table 2.3.4.1. TOP3 of Patent Applicants 75

Table 2.4.1.1. Summary of Selected Studies on the Inactivation by Chlorine Dioxide of Various Microorganisms in Water 83

Table 2.4.1.2. Summary of Trends Regarding Chlorine Dioxide Residual, and Chlorite and Chlorate Ion Concentrations in Distribution Systems 85

Table 2.4.1.3. Disinfectants Used in Europe 86

Table 2.4.1.4. Use of Disinfectants/Oxidants in U.S. Water Systems 87

Table 2.4.2.1. Management of Water Treatment for Disinfection 88

Table 3.1.1.1. Target-selection Process of Sequential Disinfection 101

Table 3.1.3.1. Rate Constant of OH Radical Molecular Ozone for Geosmin and 2-MIB 115

Table 3.1.3.2. Degradation of 2-MIB and Bisphenol-A under Ozone/H₂O₂System([O₃])0＝2 mg/L, Contact Time＝1 min, [pCBA]0＝3 mM, [Bisphenol-A]0＝3 mM, pH 6.9(10 mM))(이미지참조) 116

Table 3.1.3.3. Degradation of Contaminants under UV/H₂O₂System(IT ＝ 90 mV/㎠.sec, [H₂O₂])0＝0.4 mM, [pCBA]0＝5 mM, [1,4-Dioxane]0＝5 mM, [Bisphenol-A]0＝5 mM, [Geosminl-A]0＝5 mM, [2-MIB]0＝5 mM, pH 6.9 (10 mM))(이미지참조) 122

Table 3.2.1.1. Hydraulic Characterization Alternatives 145

Table 3.2.1.2. Disinfectant Demand/Decay Characterization Alternatives 145

Table 3.2.1.3. Inactivation Kinetic Parameter Alternatives 146

Table 3.2.1.4. DBP Alternatives 147

Table 3.2.3.1. Coefficients of Molecule Diffusion, Turbulent Diffusion and Dispersion 166

Table 3.2.3.2. Variable Dispersion Values 170

Table 3.2.4.1. Characterization Comparison of Various Inactivation Models 172

Table 3.2.5.1. Components of DBPs in Drinking Water, Their Effects and Regulatory Limits 176

Table 3.2.5.2. Models for DBPs Formation 177

Table 3.3.1.1. Giardias and Virus Inactivation Rates 182

Table 3.3.1.2. CT Values for Cryptosporidium Inactivaiton by Ozone 183

Table 3.3.1.3. Inactivation Rate by Ozone, kc, for Cryptosporidium(이미지참조) 183

Table 3.3.1.4. Giardias and Virus Disinfection Data and Calculation Results for a Convential Treatment Plant at a Water Temperature of 17 ℃ 190

Table 3.3.1.5. Giardias and Virus Disinfection Data and Calculation: Results for a Direct-filtration Treatment Plant at a Water Temperature 195

Table 3.3.1.6. Disinfection Results Using Three Residual Analyzers and Ceffulent in the CT Value Calculation(이미지참조) 196

Table 3.3.1.7. Disinfection Results Using Three Residual Analyzers and Caverage in the CT Value Calculation(이미지참조) 200

Table 3.3.1.8. Extended CSTR Cryptosporidium(Cryptosporidum) log-inactivaiton Data and Calculation Results Using k* avg(이미지참조) 202

Table 3.3.1.9. Extended CSTR Cryptosporidium log-inactivatio Data and Calculation Results Uslng k* max(이미지참조) 207

Table 3.3.1.10. Extended Integrated CT10 Cryptosporidium log-inactivation Data and Calculation Results k* max(이미지참조) 209

Table 3.3.2.1. Checklist for Ozone Generator and Contactor Sizing Optimization 212

Table 3.3.2.2. Estimated Residual Profile Using Bench-scale Demand and Decay Data 216

Table 3.3.2.3. Estimated Disinfection from Bench-scale Demand and Decay Data 219

Table 3.3.2.4. Achieved Disinfection Performance for Full-scale Plane B Measured Data 220

Table 3.3.3.1. Ways to Optimize Ozonation 231

Table 3.3.3.2. Example Plant Ozone Design and Operating Criteria 233

Table 3.3.3.3. Example Ozone Monitoring Data 234

Table 3.3.3.4. Disinfection CT Value and Giardia and Virus Credit Using Effluent Method 235

Table 3.3.3.5. Monthly Summary Report for Ozone Generation System Performance 241

Table 3.3.3.6. Monthly Summary Report for Ozone Contact Performance 242

Table 3.4.1.1. Ozone Injection Types 247

Table 3.4.1.2. Effect Factors of Ozone Treatment 250

Table 3.4.1.3. Factors for Ozone Contactor 251

Table 3.4.3.1. RT and Flow Conditions in Clearwell 275

Table 3.4.4.2. Efficiency of Disinfectants 283

Table 3.4.4.3. Group of DBPs 284

Table 3.4.4.4. Observation of Experiment Data 291

Table 3.4.4.5. Experimental Conditions for Characterizing DBP Formation Potential in Chlorine Alone and Chlorine Dioxide/Chlorine Process 298

Table 3.4.4.6. Experimental Conditions during UV Irradiation 305

Table 3.4.4.7. Observation of Experiment Data (Cl₂) 307

Table 3.4.4.8. Observation of Experiment Data (ClO₂/Cl₂) 311

Table 3.4.4.9. Observation of Experiment Data (O₃/Cl₂) 313

Table 3.4.6.1. Error Correction of Excel Program 326

Table 3.4.6.2. Improvement of CT Program 329

Table 3.4.7.1. Evaluation of CT for the Design of Ozone/Chlorine Disinfection Process 336

Table 3.4.7.2. Evaluation of CT for the Design of Ozone/Chlorine Disinfection Process 337

Table 4.1.1.1. Achievement of Research and Development 354

Table 4.1.1.2. Results of Paper and Patent (1st Year) 355

Table 4.1.1.3. Results of Paper and Patent (2nd Year) 356

Table 4.1.1.4. Results of Paper and Patent (3rd Year) 357

Table 4.3.1.1. Applied Field of Results and System 360

Figure 1.1.1.1. Giardia Cyst and Cryptosporidium Oocyst 28

Figure 1.1.2.1. Contents Scope 32

Figure 1.1.3.1. Development Direction of Project 33

Figure 1.1.3.2. Time Plan of this Project 33

Figure 2.3.2 1. Trends in Number of Patent Applications or Patent Publicized for Sequential Disinfection Technology 63

Figure 2.3.2.2. Patent Share of Four Patent Offices (Korea, Japan, EU and USA) 63

Figure 2.3.3.1. The Trend of Elongation Rate for Sequential Disinfection Patents using Patent Portfolio Analysis 66

Figure 2.3.3.2. Portfolio Analysis for Sequential Disinfection Patents (Elongation Rate vs Number of Patents) 67

Figure 2.3.3.3. Portfolio Analysis for Sequential Disinfection Patents (Number of Applicants vs Number of Patents) 69

Figure 2.3.4.1. Distribution in Resident and Non-resident Patent Fillings at Korea Patent Office 70

Figure 2.3.4.2. Distribution in Resident and Non-resident Patent Fillings at USA Patent Office 71

Figure 2.3.4.3. Distribution in Resident and Non-resident Patent Fillings at Japan Patent Office 72

Figure 2.3.4.4. Distribution in Resident and Non-resident Patent Fillings at EU Patent Office 73

Figure 2.3.4.5. Comparison of Activity Index(AI) for UV+H₂O₂Process at All Selected Patent Offices 77

Figure 2.3.4.6. Comparison of Activity Index(AI) for Ozone+UV Process at All Selected Patent Offices 78

Figure 2.3.4.7. Comparison of Activity Index(AI) for Ozone+H₂O₂Process at All Selected Patent Offices 79

Figure 2.3.4.8. Comparison of Activity Index (AI) for Ozone+Chlorine Process at All Selected Patent Offices 79

Figure 2.3.4.9. Comparison of Activity Index (AI) for Ozone+Chlorine Dioxide Process at All Selected Patent Offices 80

Figure 2.4.2.1. Turbidity Profile for Clear Well of Each Domestic WTP 91

Figure 2.4.2.2. Chlorine Residual Profile for Each of the Domestic WTPs 91

Figure 2.4.2.3. T10/T Profile for Each of the Domestic WTPs(이미지참조) 92

Figure 2.4.2.4. Profile of Giardia Inactivation Ratio for Each of the Domestic WTPs 92

Figure 2.4.2.5. Monthly Trends of Virus Inactivation Ratio for Clear Well in WTP B 93

Figure 2.4.2.6. Monthly Trends of Virus Inactivation Ratio for Clear Well to Storage in WTP B 94

Figure 2.4.2.7. Monthly Trends of Maximum Giardia Inactivation for Clear Well 95

Figure 2.4.2.8. Monthly Trends of Maximum Giardia Inactivation Ratio from Clear Well to Storage 95

Figure 2.4.2.9. Monthly Trends of Minimum Virus Inactivation Ratio for Clear Well to Storage in WTP Q 97

Figure 2.4.2.10. Monthly Trends of Minimum Virus Inactivation Ratio for Clear Well to Storage in WTP Q 97

Figure 2.4.2.11. Monthly Trends of Minimum Giardia Inactivation Ratio in WTP Q 98

Figure 3.1.1.1. Synergy Effect of Sequential Disinfection by Ozone Followed by Free Chlorine 100

Figure 3.1.2.1. Automated Control System of Sequential Disinfection Process 102

Figure 3.1.3.1. Comparison Of Synergistic Effect for Ozone/H₂O₂With Primary or Second Chlorination. (Cho et al., OS&E, 2006) 105

Figure 3.1.3.2. Schematic Diagram of Chlorination Reactor 106

Figure 3.1.3.3. UV Reactor 108

Figure 3.1.3.4. Rct Concept (Elovitzand von Gunten, Water Research, 1999) 110

Figure 3.1.3.5. Determination of OH Radical Amounts Using Rct Concept 110

Figure 3.1.3.6. Structure of 1,4-Dioxane 112

Figure 3.1.3.7. Ozone Decay for Raw Water Condition during Ozonation(DOC ＝ 1.85 mg/L, Ozone dose ＝ 2.1 mg/L, pH 7.1, Temp.＝20 ℃) 112

Figure 3.1.3.8. PCBA Degradation for Raw Water Condition during Ozonation(DOC ＝ 1.85mg/L, Ozone dose ＝ 2.1 mg/L, [pCBA]0＝2 mM, pH 7.1, Temp.＝20 ℃)(이미지참조) 113

Figure 3.1.3.9. Prediction of 1,4-Dioxane Removal during Ozonation(Raw Water ＝ Han River, DOC ＝ 1.85 mg/L, Ozone Dose ＝ 2.1 mg/L, [1.4-Dioxane]0 ＝ 2 mM, [pCBA]0＝ 2 mM, pH 7.1, Temp. ＝ 20 ℃)(이미지참조) 114

Figure 3.1.3.10. Enhanced Degradation of 1,4-Dioxane in Ozone/H₂O₂System([H₂O₂]0 ＝ 0.04 mM, Ozone Dose ＝ 2.8 mg/L, pH 7.1, Temp. ＝ 25 ℃, Contact Time ＝ 25 sec)(이미지참조) 114

Figure 3.1.3.11. Molecular Structure of Geosmin and 2-MIB 115

Figure 3.1.3.12. Prediction of Geosmin and MIB Removal during Ozonation(Raw Water ＝ Han River, DOC ＝ 1.85mg/L, Ozone dose ＝ 2.1 mg/L, [pCBA]0 ＝ 300 mg/L, pH 7.1, Temp. ＝ 20 ℃)(이미지참조) 116

Figure 3.1.3.13. Microbial Inactivation of MS-2 Phage and Bacillus Subtilis Spores with UV and UV/H₂O₂at pH 7.1(UV Intensity ＝ 0.4 mV/cm², Temp. ＝ 20 ℃) 118

Figure 3.1.3.14. Norovirus Inactivation by UV Irradiation 119

Figure 3.1.3.15. Sequential Disinfection with UV/H₂O₂Followed by Cl₂at pH 7.1(UV Intensity ＝ 0.4 mV/cm², Temp. ＝ 20 ℃) 120

Figure 3.1.3.16. Quantitative Estimation of the Sequential Disinfection 120

Figure 3.1.3.17. Degradation of pCBA under UV/H₂O₂(I ＝ 0.4 mV/cm², [pCBA]0 ＝ 5 mM, pH7).(이미지참조) 121

Figure 3.1.4.1. Cryptosporidium Refining Procedures Using Density Difference 125

Figure 3.1.4.2. In Vitro Excystation Method 126

Figure 3.1.4.3. Plaque Assay Method of MNV Virus 127

Figure 3.1.4.4. Bradford Assay during the Inactivation of Bacillus Subtilis Spore 131

Figure 3.1.4.5. Bradford Assay during the Inactivation of E.coli 132

Figure 3.1.4.6. PAGE Assay for Assaying the Disrupted Protein in E.coli Surface 133

Figure 3.1.4.7. Amount of Lipid Peroxidation as a Function of E.coli Inactivation 134

Figure 3.1.4.8. Cell Permeability Change as a Function of E.coli Inactivation Assessed Based on ONPG Hydrolysis Rate 135

Figure 3.1.4.9. Degradation of Intracellular Enzyme as a Function of E.coli Inactivation 136

Figure 3.1.4.10. TEM Image before and after 1 log Inactivation by Various Disinfectants 137

Figure 3.1.4.11. TEM Images of E.coli under OH Radical Treatment 138

Figure 3.1.5.1. Results of Tracer Test in Chlorine Reactor 139

Figure 3.1.5.2. Chlorine Decay as a Function of Time 139

Figure 3.1.5.3. Microorganism Inactivation by Chlorination 140

Figure 3.1.5.4. Pattern of Ozone Decay Curve 141

Figure 3.1.5.5. Microorganism Inactivation by Ozone Treatment 142

Figure 3.2.1.1. Concept of Integrated Disinfection Model 143

Figure 3.2.1.2. Flowchart of IDM Application 146

Figure 3.2.1.3. Samples of IDM Outputs 148

Figure 3.2.1.4. Flowchart of Integrated Disinfection Model Development 149

Figure 3.2.2.1. Guidance for Assessing the Applicability of the IDM 150

Figure 3.2.2.2. Guidance for Hydraulic Characterization Module Alternative Selection 151

Figure 3.2.2.3. Guidance for Disinfectant Demand/Decay Module Alternative Selection 152

Figure 3.2.2.4. Guidance for Inactivation Kinetic Module Alternative Selection 152

Figure 3.2.2.5. Guidance for DBP Formation Module Alternative Selection 153

Figure 3.2.3.1. C Curve of CFSTR 154

Figure 3.2.3.2. RTD Curve 155

Figure 3.2.3.3. Dirac's Delta Function (Unit Impulse Function) 160

Figure 3.2.3.4. C Curve for Ideal CFSTR 161

Figure 3.2.3.5. C Curve for CFSTR 163

Figure 3.2.3.6. Dispersion of PFR 165

Figure 3.2.3.7. C Curve of PFR Pulse Injection with Low Dispersion 168

Figure 3.a.3.8. C curve of PFR Pulse Injection with High Dispersion 169

Figure 3.2.4.1. Comparison of Inactivation Kinetics for Various Microorganisms 174

Figure 3.3.1.1. Giardia and Virus log-inactivaiton Rates Based on USEPA Tables 182

Figure 3.3.1.2. Example Vertical-baffled Bubble-diffuser Ozone Contactor 186

Figure 3.3.1.3. CT Value for Variable Water Temperature and Giardia and Virus log- inactivation Targets Using Vest- fit Equations 188

Figure 3.3.1.4. Example Ozone Residual Profile for 2-log Virus and 0.5 log Giardia log-inactivation Credit at a Water Temperature of 17 ℃ 189

Figure 3.3.1.5. Example Ozone Residual Profile for 3-log Virus and 1-log Giardia log-inactivation Credit at Water Temperature of 1 ℃ 193

Figure 3.3.1.6. Example Ozone Residual Profile for 1.0-log Cryptosporidium log-inactivaiton Credit at a Water Temperature of 18 ℃ 199

Figure 3.3.1.7. k* Example Conservative Ozone Residual Profile Using k* Maximum instead of k* Average(이미지참조) 204

Figure 3.3.1.8. Example Ozone Residual Profile for Extended Integrated CT10 Method(이미지참조) 206

Figure 3.3.2.1. Bech-scale SOT for Determining O₃Demand and Decay 213

Figure 3.3.2.2. Estimated Residual Values from Plant B Demand and Decay 215

Figure 3.3.2.3. Comparison of Bench-scale Estimated Ozone Dose versus Full-scale Measured Ozone Dose to Achieve Equivalent Disinfection Performance 221

Figure 3.3.2.4. Effect of Ozone Concentration on Ozone Production Capability 222

Figure 3.3.2.5. Capital Cost Form 225

Figure 3.3.2.6. Operating Cost Form 226

Figure 3.3.2.7. Order-of-magnitude Cost for Ozone System Based on Installed Generation Capacity(Langlais et al., 1991) 226

Figure 3.3.2.8. Order-of-magnitude Cost for Ozone Contactor 227

Figure 3.3.2.9. Estimated Unit Floor Space for Ozone Equipment 228

Figure 3.3.2.10. Completed Order-magnitude Operating Cost Form 229

Figure 3.3.3.1. Ozone Residual, CT, PR Instaneous Daily Values during a 1- Year Period at the Sebago Lake WTP, Portland, Maine 230

Figure 3.3.3.2. Unit-volume Ozone Operating Cost at Canal Road WTP, Somerset, New Jersery 232

Figure 3.3.3.3. Expected Ozone Residual Profile Exists when the Measured Residual Values Form Three Analyzers are all on the First-order Decay Curve(River Mountains WTP, Las Vegas, Nevada) 236

Figure 3.3.3.4. Unexpected Ozone Residual Profile in Contactor 2; Three Analyzer Readings Indicate Potential Problems with Residual Meter Calibration 237

Figure 3.3.3.5. Ozone Generator-measured Specific Energy Compacted to Expected Specific Energy Indicates Trends in Efficiency Performance(H. J. Mills WTP, Riverside, California) 237

Figure 3.3.3.6. Virus PR for 186 Data Points during October 2004 (R.M. Levy WTP, Lakeside, Califronia) 240

Figure 3.3.3.7. Ozone Dose and Contractor Detention Time Trend Charts from Monthly Average Data in an Ozone Data Monitoring Program(R.M. Levy WTP, Lake side , California) 242

Figure 3.3.3.8. Ozone Production, Power Demand, and Specific Energy Trend Charts from Monthly Average Data in an Ozone Data Monitoring Program (H.J. Mills Water Treatment Plant, California) 243

Figure 3.3.3.9. Giardia Disinfection PR and Ozone Dose Trend Charts from Monthly Average Data in an Ozone Data Monitoring Program(H.J. Mills Water Treatment Plant, California) 244

Figure 3.3.3.10. Concentration-based Ozone Transfer Efficiency Trend Chart from Ozone Data Monitoring Program at Plant X 244

Figure 3.3.4.1. Process Design and Operation Optimization of Ozonation Process in Drinking Water Treatment 245

Figure 3.4.1.1. Side Stream Injection System Types 248

Figure 3.4.2.1. Sequential Disinfection Contactor for Evaluating Pilot Plant 256

Figure 3.4.2.2. Schematic Diagram of 3D-LIF System 257

Figure 3.4.2.3. Data Collection of Fluorescence Images(Fluorescencedye: Rhodamine 6G)(Excitation: 526nm, Emissino: 555 nm) 258

Figure 3.4.2.4. Vignetting Effects 259

Figure 3.4.2.5. Attenuation Effects 259

Figure 3.4.2.6. Flow Chart of LIF Process 260

Figure 3.4.2.7. Example of LIF Image for the Measurement of Ozone Contactor Hydrodynamics 261

Figure 3.4.2.8. 3D -LIF of Pre-disinfection 261

Figure 3.4.2.9. 3D-LIF of Post-disinfection 263

Figure 3.4.2.10. 3D-LIF Image of Ozone Contactor 264

Figure 3.4.2.11. 3D-LIF Image of UV Reactor 265

Figure 3.4.2.12. Schematic Diagram of UV Reactor 265

Figure 3.4.3.1. Profiles of Numerical Value Vat 1 Dimension of Grid Points 268

Figure 3.4.3.2. Profiles of Numerical Value Vat 2 Dimension of Grid Points 269

Figure 3.4.3.3. Flow Chart of Simple Algorism 272

Figure 3.4.3.4. Test Results of CFD 273

Figure 3.4.3.5. Scheme of Clearwell and Inlet/outlet Fluid Flow Stream 274

Figure 3.4.3.6. Scheme of Dosing Point of Chlorine in Inlet Clearwell 275

Figure 3.4.3.7. Pattern of Fluid Flow Stream at Dosing Point of Chlorine in Inlet Clearwell 276

Figure 3.4.3.8. Velocity Field Profiles at Dosing Point of Chlorine in Inlet Clearwell 277

Figure 3.4.3.9. Concentration Profiles at Dosing Point of Chlorine in Inlet Clearwell 277

Figure 3.4.3.10. RT Profiles at Dosing Point of Chlorine in inlet Clearwell 278

Figure 3.4.3.11. Flow Pattern of Clearwell 278

Figure 3.4.4.1. Schematic of ANN 288

Figure 3.4.4.2. Schematic Diagram of Chlorine Dioxide Generation 291

Figure 3.4.4.3. Comparison of THM(at 2 log Inactivation CT value, B. Subtilis Spore) 292

Figure 3.4.4.4. Comparison of THM(at 2 log Inactivation CT Value, Giardia) 293

Figure 3.4.4.5. THM by ClO₂/HOCl (pH 7) 293

Figure 3.4.4.6. THM by ClO₂concentration for 5 hr (ClO₂/HOCl) 294

Figure 3.4.4.7. THM by ClO₂/HOCl (pH 5) 295

Figure 3.4.4.8. THM by ClO₂/HOCl (pH 9) 296

Figure 3.4.4.9. Comparison of THM (10 ℃) 296

Figure 3.4.4.10. Comparison of THM by DOC 297

Figure 3.4.4.11. Formation Pattern of THM by Real Water 299

Figure 3.4.4.12. Formation Pattern of THM by Aldrich Humic Acid 300

Figure 3.4.4.13. Formation Pattern of THM by Suwannee River Humic Acid 301

Figure 3.4.4.14. Formation Pattern of THM by Suwannee River NOM 302

Figure 3.4.4.15. Comparison of THM Formation Potential between Chlorine Alone and Chlorine Dioxide/Chlorine Process after 168 hours of Reaction 303

Figure 3.4.4.16. Comparison of HAA Formation Potential between Chlorine Alone and Chlorine Dioxide/Chlorine Process after 168 hours of Reaction 304

Figure 3.4.4.17. Comparison of THM formation Potential by UV Irradiation 306

Figure 3.4.4.18. Prediction vs Observation of MR by Cl₂ 308

Figure 3.4.4.19. Results of ANN by Cl₂ 308

Figure 3.4.4.20. Comparison of MR and ANN (1) 309

Figure 3.4.4.21. Comparison of MR and ANN (2) 310

Figure 3.4.4.22. Comparison of MR and ANN (3) 310

Figure 3.4.4.23. Prediction vs Observation of MR by ClO₂/Cl₂ 312

Figure 3.4.4.24. Schematic of ANN (ClO₂/Cl₂) 312

Figure 3.4.4.25. Results of ANN (ClO₂/Cl₂) 313

Figure 3.4.4.26. Prediction vs Observation of MR by O₃/Cl₂ 314

Figure 3.4.4.27. Results of ANN (O₃/Cl₂) 315

Figure 3.4.5.1. Schematic Diagram of Sequential Disinfection Control System 318

Figure 3.4.5.2. Apparatus of Disinfection Decay and Demand 319

Figure 3.4.5.3. Algorithms of Sequential Disinfection Control 320

Figure 3.4.5.4. Main Frame of Sequential Disinfection Control Program 321

Figure 3.4.6.1. USER Friendly Software by Example for Designing and Simulating Ozone Disinfection process 322

Figure 3.4.6.2. Example of Software 323

Figure 3.4.6.3. Estimating Programs of Ozone Contact Tank 323

Figure 3.4.6.4. Flow Chart of CT Calculation 327

Figure 3.4.6.5. Logic of CT Program 327

Figure 3.4.6.6. Diagram of CT Program 328

Figure 3.4.6.7. Method of CT Program 328

Figure 3.4.6.8. CT Program (1) 330

Figure 3.4.6.9. CT program (2) 330

Figure 3.4.6.10. CT Program (3) 331

Figure 3.4.6.11. Evaluation Program of Sequential Disinfection Process 332

Figure 3.4.6.12. Program for Deforming the Disinfectant Dose of Sequential Disinfection Process (ClO₂+HOCl) 333

Figure 3.4.7.1. Evaluation of O₃Combined with Cl₂Process (Fixed Parameter : Residual Ozone Conc., Variable Parameter : Contact Time) 338

Figure 3.4.7.2. Evaluation of O₃Combined with Cl₂Process (Fixed Parameter : Contact Time, Variable Parameter : Residual Ozone Conc.) 339

Figure 3.4.7.3. Evaluation of ClO₂Combined with Cl₂Process (Fixed Parameter : Contact Time, Variable Parameter : Residual Ozone Conc.) 340

Figure 3.5.1.1. Pilot Plant of Sequential Disinfection 341

Figure 3.5.1.2. Instrument and Control of Sequential Disinfection 342

Figure 3.5.1.3. Pictures of Pilot-Plant in P WTP 342

Figure 3.5.2.1. MMI View for Sequential Disinfection Process 343

Figure 3.5.2.2. Auto-control Algorithm for sequential-disinfection process 345

Figure 3.5.3.1. Mobile Based Monitoring and Remote System for Evaluating Sequential Disinfection Process 346

Figure 3.5.3.2. System Architecture of Application Program 348

Figure 3.5.3.3. Main Menu View inTablet PC (iPad) 348