| description abstract | This study develops an optimal design of a municipal water resource recovery facility (WRRF) to treat a high-nitrate industrial waste. The study demonstrated two basic results: first, that a numerical optimization scheme has the potential to significantly reduce construction and operating costs for wastewater treatment. Second, it demonstrated the potential for high-nitrate industrial waste to partially satisfy the electron acceptor requirement for treating municipal wastewater, whereas the wastewater reduces the demand for supplemental carbon for treating the nitrate. The optimization scheme sought to minimize an objective function, which included annualized construction costs, operating costs, and penalties for environmental performance. The optimization algorithm used was the Nelder–Mead method. This was coupled with a commercial activated sludge simulation program in an iterative calculation to predict the performance of successive process designs. The optimized process had a predicted 89% removal of total nitrogen from the combined municipal and industrial wastewater. The optimization reduced the objective function by 53% in comparison to initial designs that were manually optimized without the algorithm. The supplemental carbon requirement was reduced by 15.5% over literature values. The unique aspect of this research is the coupling of an external biological simulation model with a numerical optimization algorithm that could significantly improve the cost-effectiveness of process design along with operating costs and effluent quality. Furthermore, it demonstrates the feasibility of treating these types of wastes in a municipal facility. The results of this study indicate that coupling a numerical optimization scheme with commercial activated sludge (or other) process simulation models has the potential to make the construction and operation of treatment facilities significantly more cost effective. This study also shows that high-nitrate industrial wastewater has the potential to be treated in combination with municipal wastewater, reducing the cost of supplemental carbon for the nitrate reduction while simultaneously reducing the cost of aeration for the wastewater treatment. We began by developing a daily cost of treatment (the objective function) based on the annualized cost for design parameters such as aeration tank and clarifier size plus operating costs for aeration and pumping energy, methanol dosage, and solids disposal. Added to this were cost penalties for effluent discharge of biochemical oxygen demand (BOD), total suspended solids (TSS), and nitrogen species. The optimization scheme iteratively makes adjustments to the design parameters to seek to minimize the total costs in the objective function. The development of an objective function that includes capital and operating costs and environmental performance factors is unique to this study. | |
