2 results
Search Results
Now showing 1 - 2 of 2
Article Citation - WoS: 31Citation - Scopus: 35Comparison Between Alternating Aerobic-Anoxic and Conventional Activated Sludge Systems(Pergamon-elsevier Science Ltd, 2007) Balku, SaziyeConventional activated sludge systems ensure removal of colloidal and dissolved carbonaceous organic matter whereas alternating aerobic-anoxic systems, in addition, satisfy a further reduction in nitrogen content of wastewater. Main difference between them is that the alternating system should also include an anoxic operation mode which satisfies denitrification. In other words conventional systems are operated under aerobic conditions whereas alternating systems require a periodical change from aerobic conditions to anoxic conditions. So the most important problem in alternating systems is to find the appropriate durations for both sequences. In this study a comparison between conventional and alternating systems is considered in terms of nitrogen removal and aeration time by simulation under the same conditions together with an optimization algorithm. The results show that an activated sludge system can be operated as an alternating aerobic-anoxic system so that nitrogen removal is also possible during treatment without any additional investment or operational cost. (C) 2007 Elsevier Ltd. All rights reserved.Article Citation - WoS: 15Citation - Scopus: 18Control Vector Parameterization Approach in Optimization of Alternating Aerobic-Anoxic Systems(Wiley, 2009) Balku, Saziye; Yuceer, Mehmet; Berber, RidvanDetermination of the optimal aeration profile for an activated sludge system in which nitrification and denitrification take place sequentially in a single reactor (alternating aerobic-anoxic) is an attractive optimization problem because of complexities involved in, and high computational times required for solution. The rigorous dynamic modeling and start-up simulation of such a system, together with aeration profile optimization by an evolutionary algorithm (EA), were tackled in a previous study. In this paper an easy-to-implement dynamic optimization technique based on sequential quadratic programming method and control vector parameterization approach is provided. In comparison with EA, the proposed algorithm gives better results in shorter computation times. Copyright (C) 2009 John Wiley & Sons, Ltd.
