Application of Mathematical Modelling Techniques in Optimal Design of Wastewater Treatment Plants

Wastewater treatment plants (WWTPs) have complex processes and interrelated operations, subsequently poses multi-facet challenges in their planning and designing. Moreover, factors such as effluent concentration, flow rate, dosage of coagulants and treatment techniques influence the efficiency of the wastewater treatment process. Mathematical modeling has evidently proven to be beneficial in designing any WWTP by predicting the trend or behavior of its treatment process in terms of its input variables. Furthermore, state-of-the-art computing power, advanced mathematical models, and user-friendly software have made it effortless to model the complexities and dependencies of the treatment process. This book chapter presents a comprehensive overview of the application of mathematical modeling in the optimal design of economical and efficient wastewater treatment plant. The statistical modeling approach has been demonstrated with a generation of regression prediction models for BOD and TSS removal in tertiary wastewater treatment using coagulant Zetag-4120. Further, chapter presents the formulation of optimization problem statement of WTTP design with emphasis upon selection of objective Function, setting up constraint criterion and choosing suitable trade-offs. Data-driven optimization techniques, including artificial intelligence and machine learning, are briefly discussed. The chapter also touches upon the challenges and path-forward in the application of mathematical modeling in the field of wastewater treatment.