<p>
</p><p> Title page – – – i<br> Declaration – – – – ii <br> Certification – iii<br> Dedication – iv<br> Acknowledgements – – – – – v<br> Table of Contents – – viii<br> List of Plates – – – xv<br> List of Figures – – xvi<br> List of Tables – xxiv<br> Abbreviations and symbols – – – xxvii<br> Abstract – – – – xxxii</p><p><b>
Chapter 1
: <br>Introduction – – 1</b><br>11 Background to the study – 1<br>12 Problem statement – – – – 5 <br>13 Aim of the research – 6<br>14 Objectives – 6<br>15 Scope of study – – – 6<br>16 Justification of study – 7<br>17 Limitation of the work – – – – 7<br><b> <br>
Chapter 2
: Literature review – 8</b><br> 21 The pressure on water demand 8<br> 22 Wastewater treatment systems in use – – – – 9<br> 23 Waste stabilization ponds – 11<br>231 Treatment units in Waste Stabilization Ponds – – – 12 <br> 232 Anaerobic ponds – 13<br> 232 1 Design approach for anaerobic pond15 <br> 233 Facultative ponds – – – – 17<br> 2</p><p>331 Design criteria for facultative pond – – – 17 <br> 2332 Surface BOD loading in facultative ponds – – – 19<br> 234 Model approaches for faecal coliform prediction in facultative pond – – 20<br> 2341 Continuous stirred reactor (CSTR) model approach21<br> 2342 Dispersed flow (DF) model approach – – – 23<br> 235 Maturation Pond24<br> 24 Waste Stabilization Ponds in Some Selected Institutions in Nigeria – 26<br> 241 Waste stabilization pond in University of Nssuka, Nigeria – 29<br> 242 Waste stabilization pond in Obafemi Awolowo University, <br> Ile-Ife, Nigeria – 30<br> 243 Waste stabilization pond in Ahmadu Bello University, Zaria, <br> Nigeria – 32<br> 25 Residence time-models in waste stabilization ponds – – – 35<br> 251 Plug flow pattern – 35<br> 252 Completely mixed flow pattern – – – – 37<br> 253 Dispersed hydraulic flow regime – – – – 39<br> 26 Wind effect and thermo-stratification on hydraulic flow regime – 42<br> 27 Tracer experiment43<br> 28 Effects of baffles on the performance of waste stabilization – – 44<br> 29 Computational Fluid Dynamics Approach to Waste Stabilization Ponds – – – 48<br> 210 Laboratory scale ponds – – – – 56<br> 211 Optimization of waste stabilization pond design – – – 59 <br> 212 Summary of literature review – – – – 61<br> <br><b>
Chapter 3
:<br>Methodology – – – 62</b><br> 31 Description of the study area – – – – 62<br>32 Collection of data on Water demand – – – – 65<br> 33 Estimation of wastewater generated – – – – 66<br> 34 Study of existing wastewater treatment system – – – 66<br> 35 Analysis of wastewater samples70<br> 36 Design of the laboratory-scale plant layout – – – – 70<br> 361 Design Guidelines for the University, Ota – – – 73<br> 3611 Temperature (T) – – – – 73<br> 3612 Population (P) – – – – 73<br> 3613 Wastewater generation (Q) and Design for 20 years period – 73<br> 3614 BOD Contribution per capita per day (BOD) – – 73<br> 3615 Total Organic Load (B) – – – 74<br> 3616 Total Influent BOD Concentration (Li) – – – 74<br> 3617 Volumetric organic loading (λv) – – – 74<br> 3618 Influent Bacteria Concentration (Bi) – – 74<br> 3619 Required effluent standards – – – 74<br>37 Waste stabilization pond design – 75<br> 371 Design of Anaerobic Pond – – – – 75<br> 372 Design of Facultative pond76<br> 373 Design of Maturation Pond77<br>38 Design of Laboratory scale model – – – – 79<br> 381 Modeling of the Anaerobic Laboratory-scale pond – – 79<br> 382 Modeling of the Facultative Laboratory-scale pond – – – 81<br> 383 Modeling of the Maturation Laboratory-scale pond – – – 82<br> 39 Laboratory Studies – – 85<br> 391 Construction of the laboratory-scale waste stabilization ponds – 85<br> 392 Materials used for the construction of the inlet and outlet structures – 86<br> 393 Design of inlet and outlet structures of the WSP – – – 91<br> 394 Operation of the Laboratory-Scale waste stabilization pond – – 94<br> 395 Sampling and data collection – – – 95<br> 3951 Water temperature – – – 95<br> 3952 Influent and effluent samples – – – 95<br>310 Laboratory methods – 95<br> 3101 Feacal coliform – 96<br> 3102 Chloride – 96<br> 3103 Sulphate – 96<br> 3104 Nitrate – – 96<br> 3105 Phosphate – 96<br> 3106 Total Dissolved Solids – – – – 96<br> 3107 Conductivity – 97<br> 3108 pH – 97<br>311 Tracer Experiment – – 97<br> 3111 Determination of First Order Kinetics (K value) for Residence time <br> distribution (RTD) characterization – – – 99<br> 3112 The gamma extension to the N-tanks in series model approach – 101<br>312 Methodology and application of Computational Fluid Dynamics model – 103<br> 3121 Introduction 103<br> 3122 CFD Model Application – – – – 106<br> 31221 Simulation of fluid mechanics fecal coliform inactivation 106<br> 31222 Constants used in the application modes – – 109<br> 31223 Mesh generation for the computational fluid dynamics model110<br> 31224 Model test for the simulation of residence time distribution<br> curve in the CFD – – – 113<br> 31225 Model test for the simulation of faecal coliform inactivation in<br> the unbaffled reactor – – – – 114<br> 31226 Model test for the simulation of faecal coliform inactivation in<br> the baffled reactors – – – 116<br> 3123 Application of segregated flow model to compare RTD prediction <br> and the CFD predictions for feacal coliform reduction – 122 <br> 3124 Summary of the CFD model methodology – – – – 124<br> 3131 Optimization methodology and application – – – 125 <br> 31311 Integration of COMSOL Multiphysics (CFD) with <br> ModeFRONTIER optimization tool – – – 125<br>31312 The workflow pattern – – – – 126<br> 31313 Building the process flow – – – 127<br> 31314 Creating the application script – – 128<br> 31315 Creating the data flow – – – – 129<br> 31316 Creating the template input – – – 130<br> 31317 Mining the output variables from the output files – 131<br>3132 Defining the goals – – – – 132<br> 31321 The Objective functions for the optimization loop – – 132<br> 31322 The constraints for the optimization loop – – – 133<br> 31323 Cost objective Optimization – – – – 133<br> 31324 The DOE and scheduler nodes set up136<br> 31325 Model parameterization of input variables – – – 137 <br> 31326 DOE Algorithm – 140<br> 31327 Simplex algorithm – 140<br> 31328 Multi-Objective Genetic Algorithm II (MOGA-II) – – – – 141<br> 31329 Faecal coliform log-removal for transverse and longitudinal <br> baffle arrangements143<br> 3133 Sensitivity Analysis on the model parameters – – – 145 <br> 3134 Running of output results from modeFRONTIER with the CFD tool – – 146<br> 3135 Summary of the optimization methodology – – – – 146<br><b> <br>
Chapter 4
: Modeling results and Analysis </b><br> 41 Model results for the RTD curve and FC inactivation for unbaffled reactors – 147 <br> 42 Initial Evaluation of baffled WSP designs in the absence of Cost using CFD151<br> 421 Application of segregated flow model to compare the result of RTD <br> prediction and the CFD predictions for feacal coliform reduction – 163 <br> 43 Results of the N-Tanks in series and CFD models – – – 166<br> 431 General discussion on the results of the N-Tanks in series and CFD<br> Models – 173<br> 44 Results of some selected simulation of faecal coliform inactivation for 80%<br> Pond-width baffle Laboratory- scale reactors – – – 176<br>45 Optimization model results – 181<br> 451 The single objective SIMPLEX optimization configuration results – 181<br> 452 The Multi-objective MOGA II optimization configuration results – 195 <br> 453 Scaling up of Optimized design configuration – – 216<br> 4531 Scaling up of Anaerobic Longitudinal baffle arrangement – – 216<br> 4532 Scaling up of Facultative Transverse baffle arrangement – 218<br> 4533 Scaling up of Maturation Longitudinal baffle arrangement – 219<br> 4534 Summary of results of scaling up of design configuration – 220<br> 454 Results of sensitivity analysis for Simplex design at upper and lower <br> boundary – 220<br> 455 Results of sensitivity analysis for MOGA II design at upper and lower <br> boundary – 235<br> 456 Summary of the optimization model result – – – – 249<br> <br><b>
Chapter 5
: Laboratory-Scale WSP post-modeling results and verification of the <br> Optimized models – – – – 250<br></b>51 Introduction – 250<br>52 Microbial and physico-chemical parameters – – – 251 <br> 521 Feacal coliform inactivation in the reactors – – – 251<br> 522 Phosphate removal256<br> 523 Chloride removal – – – – 258<br> 524 Nitrate removal – – – – 259<br> 525 Sulphate removal – – – – 260<br> 526 pH variation265<br> 527 Total dissolved solids removal – – – 266<br> 528 Conductivity variation – – – – 266<br> 529 Summary of laboratory experimentation – – – 267<br><b> <br>Chapter 6: Discussion of results – – – – 269</b><br> 61 Experimental results of Laboratory-scale waste stabilization ponds <br> in series – 269<br>62 Hydraulic efficiency of CFD model laboratory-scale waste stabilization<br> ponds in series – 270<br> 63 Optimization of laboratory-scale ponds by Simplex and MOGA II <br> Algorithms – 274<br> 64 Summary of discussion – – – – 275<br> <br><b>Chapter 7: Conclusions and recommendations for further work – 277</b><br> 71 Conclusions277<br> 72 Contributions to knowledge – – – 278<br> 73 Recommendation for further work – – – 279<br> <br><b>References – 280<br> <br>Appendix A – 298</b><br> A1 COMSOL Multiphysics Model M-file for Transverse baffle <br> anaerobic reactor – – – – , – 298<br> A2 COMSOL Multiphysics Model M-file for longitudinal baffle <br> anaerobic reactor – 302<br> A3 COMSOL Multiphysics Model M-file for Transverse baffle <br> facultative reactor306<br> A4 COMSOL Multiphysics Model M-file for longitudinal baffle <br> facultative reactor – – – – 310<br> A5 COMSOL Multiphysics Model M-file for Transverse <br> Maturation reactor – – – – 314<br> A6 COMSOL Multiphysics Model M-file for longitudinal<br> Maturation reactor – – – – 318<br> <br><b>Appendix B322</b><br>B1 Transverse baffle arrangement scripting – – – 322<br>B2 Longitudinal baffle arrangement scripting – – 324</p><p><b>List of Plates</b><br>Plate 31 Tanker dislodging wastewater into the treatment chamber – – 67<br>Plate 32 The water hyacinth reed beds showing baffle arrangement <br> at opposing edges68<br>Plate 33 The inlet compartment showing gate valve – – 68<br>Plate 34 The Outfall waterway leading into the valley below the cliff – 69<br>Plate 35 Effluent discharging through the outfall into the thick <br> vegetation valley – – – – 69<br>Plate 36 Front view of the laboratory-scale pond – 88<br>Plate 37 Areal view of the laboratory-scale pond close to source of sunlight – – 88<br>Plate 38 An elevated tank serving as reservoir – 89<br>Plate 39 Inlet-outlet alternation of laboratory-scale WSP – – 89<br>Plate 310 Laboratory-scaled anaerobic ponds – – – 90<br>Plate 311 Laboratory-scaled facultative ponds – – – 90<br>Plate 312 Laboratory-scaled maturation ponds – – – 91<br>Plate 313 Inlet and outlet structure of the laboratory-scale <br> waste stabilization pond – – – 92<br>Plate 314 Two 25-mm PVC hoses linked with the T-connector – – 92<br>Plate 315 Control valves screwed to position for wastewater flow – 93<br>Plate 316 Outlet structures connected to two pieces of ½ inch hoses <br> for effluent Discharge – – – – 93<br>Plate 317 Tracer experiment with Sodium Aluminum Sulphosilicate – – 97<br>Plate 318 Tracer chemical diluting with the wastewater before <br> getting to the outlet – – – – 98<br>Plate 319 Improvement in wastewater quality along the units – – 98</p><p><b>List of Figures</b><br>Figure 21 Waste stabilization pond configurations 12<br>Figure 22 Operation of the Anaerobic Pond 14<br>Figure 23 Operation of the facultative pond 23<br>Figure 31 Bar chart of staff and student population trend 63<br>Figure 32 Template for calculating the per-capita water use 65<br>Figure 33 A sketch of the laboratory-scale WSP and operating conditions 72<br>Figure 34 Configuration of the designed WSP for Covenant University 79<br>Figure 35 Different baffle arrangements with 70% pond width <br> anaerobic pond 99<br>Figure 36 Different baffle arrangements with 70% pond width <br> facultative pond 100<br>Figure 37 Different baffle arrangements with 70% pond width<br> maturation pond 100<br>Figure 38 Data conversion for reactor length to width ratio to N for<br> N-tanks in series model 102<br>Figure 39 Description of length to width ratio for the laboratory-scale <br> model 102<br>Figure 310 Triangular meshes for the model anaerobic reactor 111<br>Figure 311 Triangular meshes for the model facultative reactor 111<br>Figure 312 Triangular meshes for the model maturation reactor 112<br>Figure 313 Model Navigator showing the application modes 113<br>Figure 314 Correlation data of the predicted-CFD and observed effluent Faecal <br> coliform counts in baffled pilot-scale ponds 115<br>Figure 315 General arrangements of conventional longitudinal baffles of <br> different lengths in the anaerobic pond 117<br>Figure 316 General arrangements of conventional longitudinal baffles of <br> different lengths in the facultative pond 117<br>Figure 317 General arrangements of conventional longitudinal baffles of <br> different lengths in the maturation pond 118<br>Figure 318 Mesh structure in a 4 baffled 70% Transverse Anaerobic reactor 118 <br>Figure 319 Mesh structure in a 4 baffled 70% Longitudinal Anaerobic reactor 119<br>Figure 320 Mesh structure in a 4 baffled 70% Transverse Facultative 119<br>Figure 321 Mesh structure in a 4 baffled 70% Longitudinal Facultative <br> reactor 120<br>Figure 322 Mesh structure in a 4 baffled 70% Transverse Maturation <br> reactor 120<br>Figure 323 Mesh structure in a 4 baffled 70% Longitudinal Maturation <br> reactor 121<br>Figure 324 Workflow showing all links and nodes in the user application <br> interface 127<br>Figure 325 Logic End properties dialogue interface 128<br>Figure 326 Data variable carrying nodes and the input variable properties <br> Dialogue interface 129<br>Figure 327 Template for the calculator properties and JavaScript <br> expression editor 130<br>Figure 328 Output variable mining interface and input template editor 131<br>Figure 329 DOS Batch properties and batch test editor for mined data 132<br>Figure 330 Constraint properties dialogue in the workflow canvas 135<br>Figure 331 Objective properties dialogue in the workflow canvas 135<br>Figure 332 DOE properties dialog showing the initial population of designs 136<br>Figure 333 Scheduler properties dialog showing optimization wizards 137<br>Figure 334 Designs table showing the outcomes of different reactor <br> configurations 144<br>Figure 335 History cost on designs table showing the optimized cost &a</p>
<br><p></p>
Project Abstract
Wastewater stabilization ponds (WSPs) have been identified and are used extensively to
provide wastewater treatment throughout the world. It is often preferred to the conventional treatment systems due to its higher performance in terms of pathogen removal, its low maintenance and operational cost. A review of the literature revealed that there has been limited understanding on the fact that the hydraulics of waste stabilization ponds is critical to their optimization. The research in this area has been relatively limited and there is an inadequate understanding of the flow behavior that exists within these systems. This work therefore focuses on the hydraulic study of a laboratory-scale model WSP, operated under a controlled environment using computational fluid dynamics (CFD) modelling and an identified optimization tools for WSP.A field scale prototype pond was designed for wastewater treatment using a typical residential institution as a case study. This was reduced to a laboratory-scale model using dimensional analysis. The laboratory-scale model was constructed and experiments were run on them using the wastewater taken from the university wastewater treatment facility.
The study utilized Computational Fluid Dynamics (CFD) coupled with an optimization
program to efficiently optimize the selection of the best WSP configuration that satisfy
specific minimum cost objective without jeopardizing the treatment efficiency. This was
done to assess realistically the hydraulic performance and treatment efficiency of scaled
WSP under the effect of varying ponds configuration, number of baffles and length to
width ratio. Six different configurations including the optimized designs were tested in the
laboratory to determine the effect of baffles and pond configurations on the effluent
characteristics. The verification of the CFD model was based on faecal coliform
inactivation and other pollutant removal that was obtained from the experimental data.
The results of faecal coliform concentration at the outlets showed that the conventional
70% pond-width baffles is not always the best pond configuration as previously reported
in the literature. Several other designs generated by the optimization tool shows that both
shorter and longer baffles ranging between 49% and 83% for both single and multi-
objective optimizations could improve the hydraulic efficiency of the ponds with different
variation in depths and pond sizes. The inclusion of odd and even longitudinal baffle
arrangement which has not been previously reported shows that this configuration could
improve the hydraulic performance of WSP. A sensitivity analysis was performed on the
model parameters to determine the influence of first order constant (k) and temperature
(T) on the design configurations. The results obtained from the optimization algorithm
considering all the parameters showed that changing the two parameters had effect on the
effluent faecal coliform and the entire pond configurations.
This work has verified its use to the extent that it can be realistically applied for the
efficient assessment of alternative baffle, inlet and outlet configurations, thereby,
addressing a major knowledge gap in waste stabilization pond design. The significance of
CFD model results is that water and wastewater design engineers and regulators can use
CFD to reasonably assess the hydraulic performance in order to reduce significantly faecal
coliform concentrations and other wastewater pollutants to achieve the required level of
pathogen reduction for either restricted or unrestricted crop irrigation