4 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 4 / 4
Öğe Performance and emission evaluation of a CI engine fueled with preheated raw rapeseed oil (RRO)–diesel blends(Journals & Books, 2010-03) Aydın, Hüseyin; Hanbey, HazarMany studies are still being carried out to find out surplus information about how vegetable based oils can efficiently be used in compression ignition engines. Raw rapeseed oil (RRO) was used as blended with diesel fuel (DF) by 50% oil–50% diesel fuel in volume (O50) also as blended with diesel fuel by 20% oil–80% diesel fuel in volume (O20). The test fuels were used in a single cylinder, four stroke, naturally aspirated, direct injection compression ignition engine. The effects of fuel preheating to 100 °C on the engine performance and emission characteristics of a CI engine fueled with rapeseed oil diesel blends were clarified. Results showed that preheating of RRO was lowered RRO’s viscosity and provided smooth fuel flow Heating is necessary for smooth flow and to avoid fuel filter clogging. It can be achieved by heating RRO to 100 °C. It can also be concluded that preheating of the fuel have some positive effects on engine performance and emissions when operating with vegetable oil.Öğe The use of waste transformer oil as alternative fuel in a diesel power generator(International Journal of Automotive Engineering and Technologies, 2019-10-31) Altun, Şehmus; Yıldız, AbdulkerimIn this study, waste transformer oil (WTO) was investigated as a fuel candidate for a diesel power generator set in terms of its fuel and combustion characteristics. Kinematic viscosity, which is the most restrictive property of WTO (9.6 mm2 /s at 40 oC), was measured on different blends with a conventional diesel fuel (in 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100% by volume) in order to detect the suitable blending ratio to be used in engine without any modification, and to propose some blending strategies to optimize engine performance and emissions. The blended fuels containing WTO up to 50% with diesel by volume were found to have a viscosity which is within standard value specified for conventional diesel fuels, i.e., 2.0-4.5 mm2 /s in EN590, and in case 60% WTO, it agrees with EN14214 (3.5-5.0 mm2 /s) alternative diesel fuel standards. It is also found that a fuel blend containing 20% WTO and 80% diesel have a kinematic viscosity and density which are very close to conventional diesel’ values. Therefore, WTO was blended with diesel at the rate of 20% by volume and then tested in a 4-stroke and 4-cylinder diesel engine powered generator set under constant speed-variable load conditions. Measured and calculated results were compared with the results of conventional diesel tested under the same conditions. Experimental results showed that specific fuel consumption, NOx and unburned HC emissions reduced when using blended fuel instead of conventional diesel. Cylinder gas pressure was higher for blended fuels than that of conventional diesel while the start of combustion was later in the case of blended fuelsÖğe Effect of biodiesel addition in a blend of isopropanol-butanol-ethanol and diesel on combustion and emissions of a CRDI engine(Taylor & Francis, 2021-05-21) Altun, Şehmus; İlçin, KutbettinThe increasing demand for energy and the fact that petroleum, which is the most used energy source, has a limited reserve, have led researchers to search for new and renewable energy sources. In this context, biofuels such as biodiesel and bio alcohols have been studied and used in internal combustion engines for a long time. However, with the developments in technology, the production and use of such alternative fuels in different engine technologies is still a subject of research. In this regard, isopropanol-butanol-ethanol (IBE) has received an increasing attention over standard alcohols and its potential as a substitute for other alcohol fuels in internal combustion engines has been researched recently. Therefore, the purpose of the experimental study is to investigate the effect of biodiesel addition at rates of 20% and 40% by volume in a blend of IBE (30% v/v) with petroleum-based diesel (70% v/v) on the combustion and emission characteristics of a single-cylinder common-rail direct injection engine at constant engine speed of 2400 rpm and 60% load conditions. Experimental results showed that all blended fuels presented a potential to reduce smoke opacity by 27% − 41%, CO emissions by 44% − 66% and unburnt HC emissions (up to 31.8%) but increase NOx emissions by 5% − 24.6% compared to diesel. However, adding biodiesel caused to a slight increase in smoke opacity and CO emissions while decrease in unburned HC and NOx emissions compared to the blend of IBE and diesel. Combustion analysis also showed that the use of blended fuels led to the increase of peak cylinder pressure (by 7%) and the significant improvement in the rate of heat release was observed, which further increased with the addition of biodiesel to blend of IBE and diesel. It was concluded that ternary blends was performed better than the blend of IBE and diesel while biodiesel addition was found to be beneficial in terms of reduction of unburnt HC and NOx emissions along with improved performance.Öğe Determining optimal artificial neural network training method in predicting the performance and emission parameters of a biodiesel-fueled diesel generator(International Journal of Automotive Engineering and Technologies, 2019-04-03) Altun, Şehmus; Ertuğrul, Ömer FarukArtificial neural network (ANN) methods were employed and suggested in modeling the emissions and performance of a diesel generator fueled with waste cooking oil derived biodiesel during steady-state operation. These papers are generally built on determining optimal network structure, but the modelling accuracy of an ANN is also highly dependent on employed training method. In modeling, operating conditions and fuel blend ratio were used as the inputs while the performance and emission parameters were the outputs. The modeling results obtained by conventional ANNs that were trained by back propagation (BP) learning algorithm, radial basis function (RBF), and extreme learning machine (ELM) were compared with experimental results and each other. The accuracy of the estimations by ELM was above 95% for all the output parameters except for specific fuel consumption and thermal efficiency. Moreover, ELM performed better than BP and RBF with lower mean relative error (MRE) in case where the emissions were estimated. The ELM provided correlation coefficients of 0.987, 0.950 and 0.996 for unburned hydrocarbons (HCs), nitrogen oxides (NOx) and smoke opacity (SO), respectively, while for BP, they were 0.973, 0.818, 0.993, and for RBF, 0.975, 0.640 and 0.981. The most suitable training function for each emission and performance parameters of diesel generator was determined based on obtained accuracies.
