Chemical Engineering / Kimya Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/14
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Article Citation - WoS: 64Citation - Scopus: 78Utilization of Municipal Plastic and Wood Waste in Industrial Manufacturing of Wood Plastic Composites(Springer Verlag, 2020) Başalp, Dildare; Tıhmınlıoğlu, Funda; Sofuoğlu, Sait Cemil; İnal, Fikret; Sofuoğlu, AysunIn this study, Wood Plastic Composites (WPCs) were produced from post-consumer bulky wastes of recycled plastic and wood in order to minimize waste, decrease environmental effects of plastics, reserve natural resources, and support circular economy for sustainable production and consumption. Five different types of polypropylene (PP) or polyethylene (PE) based recycled plastics and wood obtained from urban household bulky wastes were used in the production of recycled WPC composites, r-WPCs. Virgin WPC (v-WPC) and r-WPC compounds were prepared with wood flour (WF) and maleic anhydride grafted compatibilizer (MAPP or MAPE) to evaluate the effect of recycled polymer type and compatibilizer on the mechanical properties. It was found that tensile strength properties of r-WPCs produced from recycled PP (r-PP) were higher than that of the r-WPCs produced from mixed polyolefins and recycled PE. r-WPCs containing anti-oxidants, UV stabilizers, and compatibilizer with different WF compositions were produced from only recycled garden fraction PP (PPFGF) to determine the optimum composition and processing temperature for pilot scale manufacturing of r-WPCs. Based on tensile, impact, flexural, and water sorption properties of r-WPC compounds with different formulations, the optimum conditions of r-WPC compounds for industrial manufacturing process were determined. Surface morphology of fractured surfaces as well as tensile, flexural and density results of r-WPC compounds revealed the enhancement effect of MAPP on interfacial adhesion in r-WPCs. r-WPC products (crates and table/chair legs) based on bulky wastes were produced using an injection molding process at industrial scale by using 30 wt% WF-filled r-WPC compound. This study demonstrated that r-WPC compounds from recycled bulky plastic and wood wastes can be used as a potential raw material in plastic as well as WPC industry, contributing to circular economy. GraphicArticle Effects of Reactor Pressure and Inlet Temperature on N-butane/Dimethyl Ether Oxidation and the Formation Pathways of the Aromatic Species(John Wiley and Sons Inc., 2016) Bekat, Tuğçe; İnal, FikretOxidation of n-butane/dimethyl ether (DME)/O2/Ar system was studied by chemical kinetic modeling in a tubular reactor operated adiabatically and at constant pressure. Effects of the reactor pressure on the formation of various major, minor, and trace oxidation products were investigated for two different pressures (1 and 5 atm) and at six different inlet temperature values (700, 800, 900, 1100, 1300, and 1500 K). The analysis was carried out for two different concentrations of dimethyl ether in the inlet fuel mixture (20 and 50 mol %). Higher pressure (5 atm) resulted in higher mole fractions of methane, vinylacetylene, and cyclopentadiene; and lower mole fractions of formaldehyde, acetylene, acetaldehyde, ethane, propargyl, and propane. The mole fractions of CO and CO2 were not affected considerably by the pressure change. The main formation routes of benzene were developed at two different inlet temperature values (1100 and 1300 K), and the main precursors participating in these routes were found to be propargyl, propene, and diacetylene. A skeletal mechanism was developed for the oxidation of n-butane/DME mixture from the detailed mechanism by reduction of the elementary reactions by 79%, and it was tested for accuracy by comparison with the data from the literature.Article Citation - WoS: 28Citation - Scopus: 18Artificial Neural Network Prediction of Tropospheric Ozone Concentrations in Istanbul, Turkey(John Wiley and Sons Inc., 2010) İnal, FikretTropospheric (ground-level) ozone has adverse effects on human health and environment. In this study, next day's maximum 1-h average ozone concentrations in Istanbul were predicted using multi-layer perceptron (MLP) type artificial neural networks (ANNs). Nine meteorological parameters and nine air pollutant concentrations were utilized as inputs. The total 578 datasets were divided into three groups: training, cross-validation, and testing. When all the 18 inputs were used, the best performance was obtained with a network containing one hidden layer with 24 neurons. The transfer function was hyperbolic tangent. The correlation coefficient (R), mean absolute error (MAE), root mean squared error (RMSE), and index of agreement or Willmott's Index (d2) for the testing data were 0.90, 8.78 μg/m3, 11.15μg/m3, and 0.95, respectively. Sensitivity analysis has indicated that the persistence information (current day's maximum and average ozone concentrations), NO concentration, average temperature, PM10, maximum temperature, sunshine time, wind direction, and solar radiation were the most important input parameters. The values of R, MAE, RMSE, and d2 did not change considerably for the MLP model using only these nine inputs. The performances of the MLP models were compared with those of regression models (i.e., multiple linear regression and multiple non-linear regression). It has been found that there was no significant difference between the ANN and regression modeling techniques for the forecasting of ozone concentrations in Istanbul. Tropospheric ozone has adverse effects on human health and environment. Here, the next-day's maximum 1-h average ozone concentrations in Istanbul were predicted using multi-layer perceptron type artificial neural networks (MLP-ANNs). The MLP-ANNs were compared to multiple linear and multiple non-linear regression models. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.