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    Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Heavy Metal Inhibition on an Alternating Activated Sludge System and Its Comparison To Conventional Methods: Case Study of Cu2+
    (Iwa Publishing, 2021) Buaisha, Magdi; Balku, Saziye; Ozalp-Yaman, Seniz
    In order to understand the behaviour of wastewater treatment plants (WWTPs) with heavy metal presence, the present study evaluates the treatment process in the presence of heavy metals (Cu2+ as a case study) and compares it with the absence of heavy metals. An activated sludge model is improved by means of incorporating other novel inhibitory kinetic and settler models for this evaluation. To achieve this goal, a simulation algorithm is developed using the MATLAB code to detect any heavy metal influence on the aerobic and anoxic growth of heterotrophic and autotrophic biomass. The code also allows for a comparison of treatment plant performance with and without Cu2+ in both conventional and alternating systems. The results reveal that the presence of heavy metals, in case of the present study for Cu2+ at 0.5 mg/L, in a biological treatment system, has an inhibitory effect on the heterotrophic bacteria but more so on the autotrophic bacteria growth and it prevents nitrification and denitrification, thus negatively effecting on the nitrogen removal in the alternating systems.
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    Article
    Citation - WoS: 22
    Citation - Scopus: 23
    On the Usage of Artificial Neural Networks in Chlorine Control Applications for Water Distribution Networks With High Quality Water
    (Iwa Publishing, 2011) Soyupak, S.; Kilic, H.; Karadirek, I. E.; Muhammetoglu, H.
    Artificial neural network (ANN) methodology has found some recent applications as efficient control tools for satisfying free residual chlorine (FRC) levels at critical locations of water distribution systems. This particular research was started to critically investigate the potential and applicability of the ANN approach as a tool for controlling FRC levels for complex water distribution systems supplied by high quality waters with low chlorine demands. Konyaalti Water Distribution System, operated by Antalya Water and Wastewater Administration, Turkey, has been selected as a pilot. The selected system is complex in structure and supplied with raw water which has high quality and low decay rate of chlorine. The study has shown that ANN models with high predictive power and precision can be developed for such water distribution systems, and that these models can be utilized for forecasting purposes. The data for model building should be collected properly if the developed ANN models are to be utilized as control instruments for FRC levels within water distribution systems.