Yazar "Akyol, Ugur" seçeneğine göre listele

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    Drying kinetics of cotton based yarn bobbins in a pressurized hot-air convective dryer
    (Sage Publications Ltd, 2017) Akal, Dincer; Kahveci, Kamil; Akyol, Ugur; Cihan, Ahmet
    In this study, the drying kinetics of cotton bobbin drying process in a pressurized hot-air convective bobbin dryer was investigated, and a drying model was introduced for the simulation of drying. Tests were conducted for drying temperatures of 70?, 80?, and 90?; effective drying air pressures of 1, 2, and 3 bars; three volumetric flow rates of 42.5, 55, and 67.5 m(3)/h; and for three different bobbin diameters of 10, 14, and 18cm. Optimum drying conditions were specified in terms of drying time and energy consumption. Results indicate that the total drying time depends significantly on the drying temperature, pressure, and volumetric flow rate. Results show that the minimum energy consumption is obtained for low values of drying air temperatures and pressures, and for moderate and high values of drying air volumetric flow rates. It was also found that the Page model is suitable for simulating the drying behavior of cotton yarn bobbins. Finally, results show that effective diffusion coefficient values are between 1.132x10(-7) m(2)/s and 3.453x10(-7) m(2)/s depending on the values of drying parameters.
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    A mathematical model for through-air drying process of yarn bobbins
    (Taylor & Francis Ltd, 2022) Akyol, Ugur; Karakoca, Alper; Shaliyev, Rafayel; Kahveci, Kamil; Cihan, Ahmet
    In this study, a mathematical model has been developed to simulate the through-air drying process of yarn bobbins. For this purpose, experimental data was obtained in a prototype experimental set up by passing pressurized hot air through the wool yarn bobbins. First of all, the physical phenomenon expressing the drying process has been reduced to the heat transfer problem and then a mathematical model has been written for the drying process which also includes the convective term. Using the experimental data, the coefficient included in the mathematical model was found by the extremal method. So, an inverse problem was solved. The accuracy of the model was checked by comparing with the experimentally obtained temperature values after solving a direct heat transfer problem in the given conditions. Good correlation between the obtained model results and the experimental results shows the accuracy of the mathematical model.
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    A model for predicting drying time period of wool yarn bobbins using computational intelligence techniques
    (Sage Publications Ltd, 2015) Akyol, Ugur; Tufekci, Pinar; Kahveci, Kamil; Cihan, Ahmet
    In this study, a predictive model has been developed using computational intelligence techniques for the prediction of drying time in the wool yarn bobbin drying process. The bobbin drying process is influenced by various drying parameters, 19 of which were used as input variables in the dataset. These parameters affect the drying time of yarn bobbins, which is considered as the target variable. The dataset, which consists of these input and target variables, was collected from an experimental yarn bobbin drying system. Firstly, the most effective input variables on the target variable, named as the best feature subset of the dataset, were investigated by using a filter-based feature selection method. As a result, the most important five parameters were obtained as the best feature subset. Afterwards, the most successful method that can predict the drying time of wool yarn bobbins with the highest accuracy was explored amongst the 16 computational intelligence methods for the best feature subset. Finally, the best performance has been found by the REP tree method, which achieved minimum error and time taken to build the model.