Chemical Engineering / Kimya Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/14
Browse
20 results
Search Results
Research Project Biyolojik-kimyasal reaksiyonların benzetimi için Monte Carlo teknikleri(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2012) Altınkaya, Mustafa Aziz; İnal, Fikret; Baran, YusufKimyasal reaksiyonların stokastik modellemesi, reaksiyondaki molekül sayılarının az olduğu durumda, her bir molekülün ne zaman reaksiyona gireceğinin tam olarak belirlenememesi nedeniyle yalnızca makroskopik ölçekte doğru olan gerekirci yönteme göre daha başarılıdır. Gillespie’nin geliştirdiği stokastik benzetim algoritması (SBA) Monte Carlo teknikleriyle sistemdeki bir sonraki reaksiyonun hangi reaksiyon olacağını ve ne zaman gerçekleşeceğini belirlemektedir. Ancak SBA’nın molekül sayıları arttıkça işlem yoğunluğu çok artmaktadır. Bu durumda, sistemdeki her reaksiyonu her molekülün mevcut konsantrasyonunu koruması koşulunu bozmayacak miktarda çok kez ateşleyerek, reaksiyon sistemindeki her molekülün miktarını tau peryodu ile güncelleyen tau-atlama algoritması işlem yoğunluğunu önemli ölçüde azaltmaktadır. Her bir reaksiyon kanalının tau aralığında ateşlenme adedini belirleyen Poisson değişken, reaksiyona girme eğilimi ile tau'nun çarpımı çok büyüdüğünde Gauss gibi davranmaya başlar. Bu durumda reaksiyondaki konsantrasyonları belirleyen stokastik türev denklemi Kimyasal Langevin Denklemi’ne (KLD) karşılık gelir. KLD’deki Gauss sürecin yerine Levy (alfa) - kararlı daha dürtün bir sürecin konması, KLD’nin tanımladığı Brown hareketini Levy uçuşuna dönüştürür. Kimyasal Langevin-Levy Denklemi (KLLD) olarak tanımlanan bu denklem az sayıdaki molekülün bulunduğu biyokimyasal reaksiyonları daha iyi modelleyebilir. Maltozdan glukoz elde edilen bir Michaelis-Menten sistemi ve daha çok reaksiyon içeren laktuloz hidrolizi sırasındaki enzimatik transgalaktosilasyon reaksiyonlarında KLLD’nin SBA ve KLD’ye kıyasla daha fazla gerekirci eğriden sapmaya neden olduğu ancak aynı ortalama davranışın takip edildiği görülmektedir. Bu çalışma biyokimyasal reaksiyon benzetininde KLLD’ye dayalı tau-atlamanın kullanılabileceğini göstermiştir.Research Project İlköğretim okullarında bina-içi çevresel kalitenin değerlendirilmesi(2010) Sofuoğlu, Sait C.; İnal, Fikret; Sofuoğlu, Aysun; Odabaşı, Mustafaİzmir’de, ikisi kentsel biri yarı kentsel alanda yer alan üç ilköğretim okulunda, bina‐içi hava uçucu organik madde, yarı‐uçucu organik madde, partikül madde, partikül maddede element ve inorganik gaz kirletici derişimleri ölçülmüştür. Anket uygulaması yapılarak, bina ile ilgili semptomların yaygınlığı çalışılmıştır. Bina‐içi konfor değişkenlerinden sıcaklık ve nispi nem kullanılarak hesaplanan Bina‐içi Rahatsızlık Göstergesi çok yüksek değerler almamıştır. Bina‐içi hava CO2 derişimleri ölçülerek dersliklerde havalandırmanın yeterli olmadığı görülmüştür. Uçucu organik bileşiklerden formaldehit, benzen, naftalin, toluen ve 1,3‐diklorobenzenin yüksek bina‐içi derişimlere ulaşabildiği görülmüş, ve formaldehit ve benzenin birincil düzeyde, naftalin ve toluenin de ikincil düzeyde önemli sağlık riski yaratabileceği değerlendirilmiştir. Yarı‐uçucu organik bileşiklerden poliklorlu bifeniller (PCB) ve polibromlu difenil eterler (PBDE) grubu kirleticilerin bina‐içi havada bulundukları ve içeride kaynakları olabileği görülürken, sentetik koku bileşiklerinin bir derslikte yapılan çalışma ile okul binalarında hem gaz hem de partikül fazda bulunabildikleri ve gaz fazda önemli düzeyde derişimlere eriştikleri belirlenmiştir. İnorganik gazlardan ozon için, bulgular iç hava ozon derişimlerinin, dış hava ozonu ile ilintili olduğunu ve hassas insanlarda sağlık etkisi yaratma sınırının altında kaldığı yönündedir. Karbon monoksit ise neredeyse tüm ölçümlerde ya tespit sınırı olan 1 ppm’in altında ya da oldukça düşük derişimlerde bulunmuştur. Partikül madde için elde edilen dane sayısı – boyut dağılımları, kütle – boyut dağılımları, bina‐içi hava ve dış hava derişimi bulguları, partikül madde kaynağının dış hava olduğu ancak çocukların hareketliliği sebebiyle bina‐içi mikroçevrelerde derişimlerin dış hava derişimlerinin üzerine çıkabildiğini göstermiştir. Hesaplanan Hava Kalitesi Göstergesi ‐ PM Alt Gösterge değerleri, PM2,5 derişimlerinin “sağlıksız” sınıfında yer aldığını göstermiştir. Boyut ayırımlı kütlesel PM derişimleri göstermektedir ki, ince partiküllerin (PM2,5) çoğunluğu ultra ince partiküllerdir (PM1) ve ultra ince partiküller ince partiküllere göre sayıca 2‐5 kat daha yüksek derişimlerde bulunmaktadırlar. Partikül maddede Al, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Zn elementleri tespit edilmiş olup kütle‐boyut dağılımlarının ultra ince boyutlarında görülen zirveler, hem ağırlıklı yerküre kaynaklı hem de ağırlıklı insan aktiviteleri kaynaklı elementler için ultra ince fraksiyonun önemli olduğunu göstermiştir.Article Citation - WoS: 3Citation - Scopus: 4Detailed Chemical Kinetic Modeling of Fuel-Rich N-Heptane Flame(Elsevier, 2020) Değirmenci, Emre; Alazreg, Abdalwahab; İnal, FikretThe main purpose of this study is to model one-dimensional, premixed, laminar, burner-stabilized, fuel-rich n-heptane flame to understand its combustion characteristics. Detailed chemical kinetic modeling technique was used to obtain more information about the formation nature of emissions in n-heptane flame. A detailed chemical kinetic mechanism was generated by combining several mechanisms from the literature that related with possible products of fuel-rich n-heptane combustion. The mechanism consists of 4185 reactions and 893 species. Validations of the mechanism were done by species mole fractions of premixed laminar flames and jet stirred reactors, and ignition delay times in shock tubes. A detailed investigation of the n-heptane flame was carried out using rate of production and reaction pathway analyses. Propargyl radical (C3H3), vinylacetylene (C4H4) and acetylene (C2H2) were found as the main precursors of benzene formation. The mechanism was able to predict most of the major, minor, and trace species up to four-fused aromatic rings formed in the flame. A skeletal mechanism was also generated using Directed Relation Graph with Error Propagation (DRGEP) method. It consists of 1879 reactions and 359 species. The skeletal mechanism was in a good agreement with the detailed mechanism on the species mole fraction predictions.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: 22Citation - Scopus: 25Indoor Air Quality in a Restaurant Kitchen Using Margarine for Deep-Frying(Springer Verlag, 2015) Sofuoğlu, Sait Cemil; Toprak, Melis; İnal, Fikret; Çimrin, Arif H.Indoor air quality has a great impact on human health. Cooking, in particular frying, is one of the most important sources of indoor air pollution. Indoor air CO, CO2, particulate matter (PM), and volatile organic compound (VOC) concentrations, including aldehydes, were measured in the kitchen of a small establishment where a special deep-frying margarine was used. The objective was to assess occupational exposure concentrations for cooks of such restaurants. While individual VOC and PM2.5 concentrations were measured before, during, and after frying events using active sampling, TVOC, PM10, CO, CO2, temperature, and relative humidity were continuously monitored through the whole period. VOC and aldehyde concentrations did not increase to considerable levels with deep-frying compared to the background and public indoor environment levels, whereas PM10 increased significantly (1.85 to 6.6 folds). The average PM2.5 concentration of the whole period ranged between 76 and 249 μg/m3. Hence, considerable PM exposures could occur during deep-frying with the special margarine, which might be sufficiently high to cause health effects on cooks considering their chronic occupational exposures.Article Citation - WoS: 15Citation - Scopus: 18Preparation and Characterization of Magnesium Stearate, Cobalt Stearate, and Copper Stearate and Their Effects on Poly(vinyl Chloride) Dehydrochlorination(John Wiley and Sons Inc., 2015) Gönen, Mehmet; Egbuchunam, Theresa Obuajulu; Balköse, Devrim; İnal, Fikret; Ülkü, SemraPreparation and characterization of pure metal soaps and investigation of their effects on poly(vinyl chloride) (PVC) dehydrochlorination were the objectives of the present study. Magnesium stearate (MgSt2), cobalt stearate (CoSt2), and copper stearate (CuSt2) were prepared by a precipitation method. An aqueous sodium stearate (NaSt) solution was mixed at 500 rpm with respective metal salt solutions at 75oC. The precipitates that formed were collected by filtration, washed with water, and ultimately dried at 105oC under reduced pressure. Lamellar crystals that melted on heating were obtained. Solid-liquid phase transitions were observed by optical microscopy at 160oC, 159oC, and 117oC for MgSt2, CoSt2, and CuSt2, respectively. However, the melting points of MgSt2, CoSt2, and CuSt2 were determined as 115oC, 159oC, and 111oC, respectively, by analysis by differential scanning calorimetry. The onset temperature of the mass loss was the lowest at 255oC for CuSt2 and the lowest activation energy for thermal decomposition was 18 kJ/mol for CuSt2. CoSt2 was effective in extending the induction time of PVC dehydrochlorination at both 140oC and 160oC. The activation energy calculated from stability time decreased from 175 kJ/mol for a blank PVC sample to 114, 105, and 107 kJ/mol for MgSt2, CoSt2, and CuSt2-containing PVC samples, respectively. All three metal soaps accelerated the dehydrochlorination of PVC. J. VINYL ADDIT. TECHNOL., 21:235-244, 2015.Article Citation - WoS: 37Citation - Scopus: 38Prediction of the Bottom Ash Formed in a Coal-Fired Power Plant Using Artificial Neural Networks(Elsevier Ltd., 2012) Bekat, Tuğçe; Erdoğan, Muharrem; İnal, Fikret; Genç, Aytenhe amount of bottom ash formed in a pulverized coal-fired power plant was predicted by artificial neural network modeling using one-year operating data of the plant and the properties of the coals processed. The model output was defined as the ratio of amount of bottom ash produced to amount of coal burned (Bottom ash/Coal burned). The input parameters were the moisture contents, ash contents and lower heating values of the coals. The total 653 data were divided into two groups for the training (90% of the data) and the testing (10% of the data) of the network. A three-layer, feed-forward type network architecture with back-propagation learning was used in the modeling study. The activation function was sigmoid function. The best prediction performance was obtained for a one hidden layer network with 29 neurons. The learning rate and the tolerance value were 0.2 and 0.05, respectively. R2 (coefficient of determination) values between the actual (Bottom ash/Coal burned) ratios and the model predictions were 0.988 for the training set and 0.984 for the testing set. In addition, the sensitivity analysis indicated that the ash content of coals was the most effective parameter for the prediction of the ratio of bottom ash to coal burned.Article Citation - WoS: 8Citation - Scopus: 9Effects of Dimethyl Ether on N-Butane Oxidation(Elsevier Ltd., 2014) Bekat, Tuğçe; İnal, FikretDimethyl ether (DME) is the simplest ether and it is used as an alternative fuel or fuel additive to reduce toxic emissions from combustion processes. The effects of DME on n-butane oxidation were investigated for two different concentrations of DME in the fuel mixture (i.e., 20% and 50%) and two different fuel-rich equivalence ratios (i.e., 2.6 and 3.0) using detailed chemical kinetic modeling. Reactor model was selected as atmospheric-pressure, adiabatic, tubular reactor, operated under laminar flow conditions. The concentration profiles of major, minor, and trace species were obtained for n-butane/DME/oxygen/argon at six different reactor inlet temperatures, and the results were compared with those attained for pure n-butane oxidation case (n-butane/oxygen/argon). Dimethyl ether addition decreased formations of various toxic species such as carbon monoxide, aromatic species, and polycyclic aromatic hydrocarbons, while it increased the formations of formaldehyde and acetaldehyde. Increasing equivalence ratio increased the formations of carbon monoxide, methane, aromatic species, and polycyclic aromatic hydrocarbons, while its effects on formaldehyde and acetaldehyde were not pronounced under the conditions studied.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.