Yazar "Demirpolat, Ahmet Beyzade" seçeneğine göre listele
Listeleniyor 1 - 5 / 5
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Drying behavior for Ocimum basilicum Lamiaceae with the new system: exergy analysis and RSM modeling(Springer, 2021) Demirpolat, Ahmet Beyzade; Aydoğmuş, Ercan; Arslanoğlu, HasanIn this study, drying kinetics of Arapgir purple basil leaves under the isothermal and non-isothermal conditions have been investigated. Effective methods were evaluated by drying freshly collected basil leaves in the sun, isothermal, and non-isothermal systems. Energy efficiency was compared in different drying processes by performing exergy analysis in the drying process. It has been observed that the energy consumed and lost especially in the convection drying system (tray dryer) is very high. In the experiments performed in the PID (proportional integral derivative) system, the lowest efficiency was found in the isothermal process. Accordingly, the most suitable system in exergy efficiency was determined as the non-isothermal PID system. Maximum energy loss and minimum exergy efficiency were found at 45 °C temperature and 3.0 m/s airflow rate in the convection drying process. Exergy efficiencies were found to be approximately 4% in the convection tray dryer, 26% in the PID system under isothermal conditions, and 32% in the PID system under non-isothermal conditions. Optimization parameters in the drying process were determined by the response surface methodology (RSM), and the kinetic models were compared with the help of statistical analyses in the experiments. Midilli and Kucuk model has been found as the most compatible kinetic equation with the experimental data. According to this model results, correlation coefficient (R2?>?0.990), sum of squared error (SSE?0.005), chi-square (?2?1·10?5), and root mean square error (RMSE?0.003) values have been evaluated.Öğe Effects of Different Turbulators on Heat Transfer in Smoke Tube Boilers and Modeling of These Effects with Machine Learning Algorithms(Igdir University, 2021) Çıtlak, Aydın; Demirpolat, Ahmet BeyzadeIn smoke pipe boilers, the thermal efficiency of the boiler depends on the smoke pipe diameter, smoke pipe length and the heat transfer between the smoke pipe and the outlet chimney. If the heat in the smoke pipes is effectively transported through the pipes, the heat distribution on the surfaces is balanced and the thermal efficiency of the boiler increases. In this study, the improvement of heat transfer in a solid fuel boiler with 125,000 kcal / h heat capacity with a diameter of 42 mm, chimney diameter of 230 mm and water inlet and outlet diameters of 65 mm was investigated by using 4 different types of strip turbulators. Experiments were carried out with turbulators placed in all the smoke pipes in the boiler. Firstly, experiments were carried out without placing a turbulator inside. In the second step, by placing turbulators in the smoke pipes, experiments were made for each type and heat transfer was calculated. In the experiments, the flow rate of the fan was changed with the help of damper and the reynolds number was calculated between 18000 and 28000. Turbulator experiments for heat transfer improvement have increased by at least %15 and at most %41 compared to turbulator free experiments. For the heat transfer increase values obtained because of calculations, predictive models were obtained using machine learning algorithms SVM (support vector machine) and decision tree (M5P model tree). The resulting models have been analyzed for error analysis and have been shown to successfully predict heat transfer increase values.Öğe Investigation and prediction of ethylene Glycol based ZnO nanofluidic heat transfer versus magnetic effect by deep learning(Elsevier Ltd, 2021) Demirpolat, Ahmet BeyzadeIn this study, ZnO (zinc oxide) nanoparticle production was performed. Heat transfer coefficients (h) were measured for Ethylene Glycol Based ZnO nanofluids that were produced using pure water, ethanol, and ethylene glycol materials. In the literature, this is the first study in which Nanofluid was produced and experimental results were estimated by using LSTM and CNN-LSTM deep learning models. The study graphs’ show the relationship between heat transfer coefficients. Besides, Reynolds numbers were drawn and predictive models were created by using the LSTM and CNN-LSTM deep learning models for h values of nanofluids. In addition, the deep learning architecture that predicts the effects of the magnetic effect on the heat transfer coefficient has been introduced to the literature as an innovation. The results showed that the heat transfer coefficients can be estimated with the LSTM and CNN-LSTM deep learning model with an average error of 0.7342% and 0.2001% respectively. In addition, the relative error of the heat transfer coefficients as a result of the magnetic effect was determined as 0.02944 and 0.01701, respectively, with the same methods and model. Applying the magnetic effect to the system, an irregularity was observed in the flow and as a result of increased heat transfer, the friction on the pipe wall increased. The importance of the study is modeling the heat transfer coefficient values depending on the different pH values that were used during the synthesis of ZnO nanomaterial and observing the effects of the magnetic effect on the system.Öğe Isothermal and non-isothermal drying behavior for grape (Vitis vinifera) by new improved system: exergy analysis, RSM, and modeling(Springer, 2021) Aydoğmuş, Ercan; Demirpolat, Ahmet Beyzade; Arslanoğlu, HasanIn this study, drying of grape (Vitis vinifera) in isothermal and non-isothermal conditions has been done with the newly improved proportional integral derivative (PID) system. The average energy efficiency has been calculated in the processes in which the grapes are dried is 53.4% in the isothermal PID system, 59.7% in the non-isothermal PID system, and 30.5% in the tray dryer (forced convection). To maximum exergy efficiency in the tray dryer, the experimental optimization is made according to the response surface methodology (RSM). In the RSM design, the results have been evaluated by working at different airflow rates (1.5 m/s, 2.2 m/s, 2.9 m/s) and different temperatures (298 K, 308 K, and 318 K). In natural conditions, the drying of grapes took approximately 8 days in the sun and 11 days in the shade. A new shrinkage model has been improved based on the transformation rate, considering the drying behavior of grape grains. The consistency of the obtained model equation with the experimental data has been determined with the help of statistical analysis (R2 0.9987, SST 0.0098). Moreover, when the diffusion behavior of grapes has been investigated, it is determined that both temperature and airflow rate increase the effective diffusion coefficient in the tray dryer. The maximum effective diffusion coefficient in the tray dryer is 2.11·109 m2/s at a temperature of 318 K and an airflow rate of 2.9 m/s.Öğe Malzeme cinsi farklı boruların zamana bağlı basınç düşümlerinin deneysel ölçülmesi, sayısal analizi ve anova analizi kullanılarak sınıflandırılması(Gazi Üniversitesi, 2020) Demirpolat, Ahmet Beyzade; Alıç, ErdemBu çalışmada malzeme cinsi farklı borularda gerçekleşen iç akıştaki basınç değişimleri deneysel ve sayısal olarak araştırılmıştır. Çalışmada için 2000 mm uzunluğunda 5 farklı malzemeden üretilmiş borular kullanılmıştır. Akışkan debisi değiştirilerek farklı Reynolds sayıları (Re = 45832,12- 51276,56) elde edilmiştir. Reynolds sayısının değişimi ile boru boyunca basınç değişimi deneysel olarak gözlemlenmiştir. Akışın debi değişim aralıkları, sabit hacimli bir su deposunun dolum süreleri değiştirilerek ayarlanmıştır. Kurulan deney setinin 3B modeli SOLIDWORKS 2018’de oluşturulmuş olup sayısal modeli için ANSYS FLUENT 18.1 sayısal analiz programı kullanılmıştır. Alüminyum pürüzsüz boru için elde edilen deneysel veriler, sayısal analiz ile %1’den daha az hata ile modellenmiştir. Deney seti sayısal analiz ile doğrulanmıştır. Bu deney seti üzerine diğer borular monte edilerek boru boyunca ve zamana bağlı basınç değişimleri deneysel olarak gözlemlenmiştir. Akış hızı ve basınç ölçüm aralıklarının uygunluğu, sınıflandırılmanın doğruluğu ANOVA tekniği analiz metodu ile desteklenmiştir. Sonuç olarak, uygun akış değişimi, boru çapı aralıkları ve boru malzemesi sınıflandırmaları literatüre katkı olarak sunulmuştur. Boru malzemeleri sert metaller (demir, galvanizli çelik vb.), yumuşak metaller (bakır, alüminyum vb.) ve plastik (PPRC vb.) olarak sınıflandırılabileceği gözlemlenmiştir.
