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Simulation and Optimization Algorithm To Determine The Design Parameters Of Novel Alternating Activated Sludge Systems For Removal Of Heavy Metals By Using Magnetic Nanoparticle(S)

Oluşturulma Tarihi: 01-04-2019

Niteleme Bilgileri

Tür: Tez

Alt Tür: Yüksek Lisans Tezi

Yayınlanma Durumu: Yayınlanmamış

Dosya Biçimi: PDF

Dil: İngilizce

Konu(lar): TEKNOLOJİ, Kimya mühendisliği,

Yazar(lar): Buaisha, Magdi (Yazar),

Emeği Geçen(ler): Balku, Şaziye (Danışman),

Anahtar Kelimeler

ANN, ASM3, waste water treatment, alternating activated sludge systems, heavy metals, magnetic nanoparticles


Özet

Heavy metals in wastewater influence the performance of the treatment plant and if they are not removed, impact the environment and the human health. In order to understand the optimal conditions of the removal and the effect of heavy metals on the wastewater treatment plant, this thesis is presented in two parts. In the first part, a unique modeling technique is proposed using the most recent approach involving the application of ANNs (artificial neural networks). In this way, we compare the predictions obtained with the empirical outcomes and use them as an error predictor in adsorption process. To develop the model, the experimental data extracted from three case studies in the literature has been used on the removal of heavy metals from wastewater by magnetic nanoparticles. The findings reveal that the experimental results and the predicted ones using ANN are highly compatible with each other. In the second part of this study, a simulation algorithm is developed using MATLAB to detect copper (Cu) influence on the aerobic and anoxic growth of heterotrophic and autotrophic biomass in conventional and alternating activated sludge systems. The results indicate that presence of Cu inhibits nitrification and denitrification and, hence, it has a negative effect on the nitrogen removal process in alternating systems. Overall, the following outcomes are reached. The proposed ANN model can be used as a tool for the removal of heavy metals by magnetic nanoparticles before biological treatment of waste water. ASM3 can predict and evaluate the operation of an activated sludge system that receives the effluent from an industrial plant. However, this is only under the condition that the model is improved in order to accommodate the effects of important parameters subject to and depending on the characteristics of the specific industry.


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