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Öğe Biodiesel Fuels Produced from Poppy and Canola Oils, Experimental Investigation of the Performance and Emission Values of the Samples Obtained by Adding New Types of Nanoparticles(Maik Nauka/Interperiodica/Springer, 2022) Demirpolat, Ahmet Beyzade; Uyar, Muhammed Mustafa; Arslanoglu, HasanIn this study, poppy oil and canola oil were subjected to acid and base catalysed transesterification reactions and biodiesel fuels were obtained. In addition, tests of the additive-free state of standard diesel fuel and biodiesel were also performed for comparison. These fuels have been subjected to performance and emission tests in a direct injection three-cylinder diesel engine. These values are compared with the values of standard diesel fuel. According to the results obtained from engine tests, the biodiesel produced with poppy, canola oil, and nanoparticle additives generally showed similar properties with diesel fuel. In terms of volume, the increase in the biodiesel ratio in diesel fuel has been found to increase the specific fuel consumption and exhaust outlet temperature values. By using biodiesel-containing fuels, compared to diesel fuel, CO, HC, smoke emissions decreased, NOx, CO2, and O-2 increased. Biodiesel fuel samples with additives were obtained by adding a new type of CuO nanoparticle produced in the study to biodiesel-containing fuels. Comparison of the biodiesel samples and the fuel created by adding nanoparticles to these samples with the addition of nanoparticles, it has made a great contribution in the desired direction in the consumption of approximately 20% CO, 27% HC, 29% smoke (soot), and 16% specific fuel consumption. As an innovation to the literature, improvement in combustion and performance characteristics of biodiesel with nanoparticle additive, decrease in emission values and positive effect of this decrease on the environment were observed as a result of the study.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 Experimental Investigation and Artificial Intelligence-Based Modeling of Novel Biodiesel Fuels Containing Hybrid Nanoparticle Additives(Mdpi, 2026) Uyar, Muhammed Mustafa; Demirpolat, Ahmet Beyzade; Citlak, AydinThis work investigates the influence of hybrid NiO-SiO2 nanoparticles on the engine behavior of biodiesel derived from waste sunflower oil and evaluates the experimental outcomes using a data-driven modeling approach. Biodiesel was produced via transesterification and doped with nanoparticles at concentrations of 50, 75, and 100 ppm. Performance and emission tests were conducted on a single-cylinder diesel engine operating at constant speed under varying loads. Specific fuel consumption, brake thermal efficiency, CO, HC, NOx, smoke opacity, and exhaust gas temperature were recorded and analyzed. The incorporation of nanoparticles improved combustion quality and contributed to substantial reductions in harmful emissions. The WSOB20 blend containing 100 ppm NiO-SiO2 provided the most balanced results, decreasing CO, HC, and smoke emissions by 39.50%, 39.40%, and 35.20%, respectively, relative to diesel fuel, while preserving competitive thermal efficiency. A linear regression model developed for CO prediction produced a low mean squared error (1.08 & times; 10(-5)), indicating strong predictive capability. The findings confirm that hybrid nanoparticle additives can enhance biodiesel performance while supporting accurate emission forecasting.Öğe Experimental Investigation of Biodiesel Fuels Obtained by Enriching the Content of Vegetable and Waste Oils with Nanoparticles and Modeling of Data Obtained from the Produced Fuel Samples Using Artificial Intelligence(Mdpi, 2025) Demirpolat, Ahmet Beyzade; Uyar, Muhammed Mustafa; Citlak, AydinThe objective of this study is to investigate the effects of Mn2O3 nanoparticle additives on the performance and emission characteristics of biodiesel fuels produced from vegetable- and waste-based oils. Biodiesel fuels were synthesized via the transesterification process, after which Mn2O3 nanoparticles were blended in different concentrations (50, 75, and 100 ppm). The prepared fuels were tested in a single-cylinder diesel engine operating under constant speed and variable load conditions. Engine performance parameters such as specific fuel consumption (SFC) and thermal efficiency, along with emission indicators including CO, HC, NOx, smoke opacity, and exhaust gas temperature, were systematically analyzed. Additionally, the experimental findings were modeled and validated using the machine learning-based linear regression method. The addition of Mn2O3 nanoparticles significantly improved combustion and emission performance. Among all samples, the COB10+ 100 ppm Mn2O3 fuel exhibited the best overall performance, achieving a 37.50% reduction in CO, 38.8% reduction in HC, and 33.84% reduction in smoke (soot) emissions compared to conventional diesel. This fuel also demonstrated an increase in thermal efficiency comparable to that of diesel. The improvement in thermal efficiency was attributed to enhanced the in-cylinder temperature, reduced ignition delay, and shorter combustion duration. Furthermore, the use of waste-derived vegetable oils contributed to lower production costs and a reduction in environmental impact. The linear regression model yielded an optimum prediction accuracy with a mean squared error of 5.86 x 10(-6) for CO emission data. These findings indicate that Mn2O3 nanoparticles can effectively enhance the performance and sustainability of biodiesel fuels while maintaining economic and ecological advantages.Öğe Heat transfer with MgO nanofluid in laminar flow: experimental study and ANSYS modeling(Springer, 2025) Demirpolat, Ahmet Beyzade; Uyar, Muhammed Mustafa; Arslanoglu, HasanDifferent methods are currently being developed to regulate energy cycle systems and to maximize the utilization of the energy resources available to us. In this context, other methods are being developed to use heat transfer more effectively to utilize energy more beneficially in in-pipe flows. In study, the heat transfer coefficient (h) values were determined by using MgO nanoparticles together with pure water, ethanol, and ethylene glycol materials in the nanofluid experimental setup. In the continuation of the experimental study, the variation of the heat transfer coefficient according to the Reynolds number was examined through experimental modeling in the ANSYS program using MgO nanofluid. In line with these calculations, it is observed that when MgO nanofluid is used in the system, the heat transfer value increases positively compared to pure water. Under the same conditions, when MgO nanofluid was used, the flow was laminar and heat transfer was achieved without turbulence. In conclusion, the use of nanofluid in thermal systems is of great importance, as the data we obtained reveal. In study, analyzing the experimental results of the MgO nanofluid we produced and modeling the results with ANSYS FLUENT software contributes to the literature as an innovation.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 Investigation of performance and emission values of biodiesel fuels produced by adding ZnO nanoparticles as additives to waste sunflower and Kohnu grape seed oil(Springer, 2023) Uyar, Muhammed Mustafa; Demirpolat, Ahmet Beyzade; Arslanoglu, HasanBiodiesel was produced by adding ZnO nanoparticles as additives to the waste sunflower and kohlrabi grape seed oil. As a result of the examination of the produced fuels, it was observed that there was a decrease in CO, HC, and smoke emissions and an increase in NOx, CO2, and O-2. When these nanoparticle-doped fuel samples were compared with standard diesel fuel, improvements in emission values were obtained by adding ZnO nanoparticle additives to biodiesel fuel. These improvements were observed as a 35% reduction in CO, a 40% reduction in HC, and a 45% reduction in smoke (soot). The reason for this is that the nanoparticle additive increases the heat transfer coefficient of biodiesel fuel. Accordingly, it has a positive effect on in-cylinder temperature, pressure, ignition delay, and combustion time. It was concluded that the nanoparticle additive added to the fuel together with the observed reductions in emission rates provides a great benefit to the environment. In addition, an 11% reduction in specific fuel consumption was observed thanks to this nanoparticle additive. An improvement was observed in the emission values to the environment.Öğe Investigation of performance and emission values of new type of fuels obtained by adding MgO nanoparticles to biodiesel fuels produced from waste sunflower and cotton oil(Elsevier, 2024) Uyar, Muhammed Mustafa; Citlak, Aydin; Demirpolat, Ahmet BeyzadeBiodiesel was produced using the transesterification method from waste sunflower and cotton oil. As a result of the analysis of the new type of nanoparticle-added biodiesel fuels we produce, the parameters with a decrease in emissions are CO, HC, and smoke emissions. There is a partial increase in NOx emissions. In addition, nanoparticle addition made a positive contribution by increasing thermal efficiency. The produced MgO nanoparticledoped biodiesel fuel samples were compared with diesel fuel. As seen in these comparisons, nanoparticle additives contributed positively to reducing emission values. These improvements were observed as a 31.25 % reduction in CO in the WSOB5+ 100 ppm MgO fuel sample, 41.6% reduction in HC in the COB5+ 100 ppm MgO fuel sample and 36.92% reduction in smoke (soot) in COB5+ 100 ppm MgO fuel sample. A comparison was made between the fuel samples in our study, biodiesel produced from waste sunflower and cotton, and fuels produced with nanoparticle additives of 50, 75, and 100 ppm. It was observed that the most efficient fuel sample in terms of emission values and performance was COB5 + 100 ppm MgO nanoparticle additive fuel. The biodiesel fuel sample produced with COB5 + 100 ppm MgO nanoparticle additives provided a 3.25% improvement in thermal efficiency compared to biodiesel without additives. A positive effect on the heat transfer coefficient was observed as a result of the data on the new type of nanoparticle doped biodiesel. With the impact of this contribution, parameters such as positive contribution to in-cylinder temperature, ignition delay, and combustion time were positively affected in the same direction. Another positive effect of nanoparticle additive to biodiesel, thermal efficiency, increased by 1.1 % in the COB5 + 100 ppm MgO fuel sample. Depending on the decrease in emission rate, it was concluded that the nanoparticle additive added to the fuel greatly benefits the environment.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.
