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Article Influence of Temperature on Activated Sludge Systems(2018) Balku, ŞaziyeThe present study aims to determine the influence of temperature in the treatment efficiency of the activated sludge systems. To reach this aim, a simulation study is performed using Matlab® programming language. A biological tank is modelled by the ASM3 (activated sludge model No. 3) and a settling tank is modelled by Takács settling velocity model. For a defined inflow rate and inlet waste water characteristics with the predefined design and operational parameters, the treatment model is simulated. The changes in the kinetic parameters by temperature are estimated from the values given in ASM3 and the dissolved oxygen saturation concentration in water is also concerned as a function of temperature. All the other design and the operational conditions are kept constant during simulations. The simulation algorithm is executed for the temperatures 0°C, 10°C, 20°C, and 30°C. The results show that chemical oxygen demand and total suspended solids reduce slightly with increasing temperature, however, the total nitrogen content in the effluent is changing, first increases for the temperatures 10°C, 20°C, and then decreases for 30°C when it is compared to that of at 0°C. The change in temperature affects mostly the ammonium concentration in the waste water treatment systems.Article Citation - WoS: 7Citation - Scopus: 10Ann-Assisted Forecasting of Adsorption Efficiency To Remove Heavy Metals(Tubitak Scientific & Technological Research Council Turkey, 2019) Buaısha, Magdi; Balku, Şaziye; Yaman, Şeniz ÖzalpIn wastewater treatment, scientific and practical models utilizing numerical computational techniques suchas artificial neural networks (ANNs) can significantly help to improve the process as a whole through adsorption systems.In the modeling of the adsorption efficiency for heavy metals from wastewater, some kinetic models have been used such as pseudo first-order and second-order. The present work develops an ANN model to forecast the adsorption efficiency of heavy metals such as zinc, nickel, and copper by extracting experimental data from three case studies. To do this, we apply trial-and-error to find the most ideal ANN settings, the efficiency of which is determined by mean square error (MSE) and coefficient of determination (R2). According to the results, the model can forecast adsorption efficiency percent (AE%) with a tangent sigmoid transfer function (tansig) in the hidden layer with 10 neurons and a linear transferfunction (purelin) in the output layer. Furthermore, the Levenberg–Marquardt algorithm is seen to be most ideal for training the algorithm for the case studies, with the lowest MSE and high R2 . In addition, the experimental results and the results predicted by the model with the ANN were found to be highly compatible with each other.Article Thermal Efficiency Optimization for a Natural-Gas Power Plant(2017) Balku, ŞaziyeEnergy production from fossil fuels has been regarded as the main source of the climatechange. The reason for that is the oxidation of carbon in fossil fuels to carbon dioxide duringcombustion and the highest percentage of greenhouse gases in atmosphere belongs to carbondioxide. Amongst the fossil fuels natural gas is preferred due to its low emission of greenhousegases and having no particulate matter after combustion. While the other fossil fuels emit mainlycarbon dioxide during the combustion process; natural gas emits mostly water together withcarbon dioxide. Around 22 % of the world’s electricity is produced by natural gas and this shareis expected to increase in near future. The power plants operating with natural gas as a gas cycleconsisting of a compressor, a combustion chamber and gas turbine are combined with a vaporcycle in order to increase the efficiency. A heat recovery steam generator is used to reach this aimin recent years in generating steam by the heat received from the combustion gases leaving the gasturbine. It is very important to design and operate such energy conversion systems fired by naturalgas in optimal conditions. If the efficiency can be increased, it can be said that the energetic,economic, and environmental aspects also improve. The modeling and optimization studies for acombined gas-vapor power plant are studied and the most important parameters which influencethe efficiency are determined. The results indicate that the most effective parameters from theviewpoint of efficiency are air/fuel ratio, gas/steam ratio and the pressure ratios of the compressorand, thus, the gas turbine. The thermal efficiency increases by 18.25 % and, in the meantime,the exergy destroyed decreases by 9.84 % using optimum design parameters determined by theoptimization algorithm proposed.
