Erdi Tosun

Prediction of density and kinematic viscosity of biodiesel by artificial neural networks

ABSTRACT Environmental pollution is one of the biggest issues all over the world. For this reason, researchers try to find alternative fuels for diesel engines, and biodiesel is the most profitable alternate fuel for diesel engines. In this study, biodiesel produced from cotton oil was used. The produced cotton oil biodiesel was mixed with diesel fuel at volumetric fraction of 20, 30, 40, 50, and 75%. Viscosity and density values at different temperatures for each fuel and blends were determined experimentally. Then, artificial neural network technique was used to predict viscosity and density. In this way, temperature and blend ratio were used as input for prediction of fuel properties. To train network, 85% of total data were used, and the remaining 15% of data were used to test prediction performance of structure. Results were compared with linear regression modelling. As a result, artificial neural network gave more accurate results than linear regression and can be suggested as good a prediction method.

PERFORMANCE, EMISSION AND EFFICIENCY ANALYSIS OF A DIESEL ENGINE OPERATED WITH DIESEL AND DIESEL-ETHANOL (E20) BLEND

Conventional fossil fuel sources face with scarcity risk. Therefore, researchers are trying to find new renewable alternative energy sources which have potential to replace conventional sources. MATTER: International Journal of Science and Technology ISSN 2454-5880 Available Online at: http://grdspublishing.org/ 52 Alcohol and biodiesel are prominent sources among others. In this study, performance and emission characteristics of a diesel fuel and ethanol added (20% vol.) diesel fuel (E20) operated compression ignition engine was studied in between 1000 2600 engine speed. Torque, power, specific fuel consumption curves as performance and carbon monoxide (CO), nitrogen oxides (NOx) curves as emission parameters with respect to engine speed were obtained. Energy and exergy efficiency curves versus engine speed in order to assess the system thermodynamically were also obtained. Results showed that, while torque, power, CO emission were decreased, specific fuel consumption, NOx emission were increased with use of diesel-ethanol blends. On the other hand, both energy and exergy efficiency values were decreased when alcohol was added to diesel fuel.

Finite Element Analysis of Electric Bike Rims Coupled with Hub Motor

In this study, static and fatigue analysis of three different electrical bikes’ rim which are coupled with electrical hub motor was investigated. Loading conditions were applied on rim in order to simulate driving forces that exert on road conditions. Analysis results of three rims were compared with each other. According to results, sharp edges increase von-Mises stresses and decrease fatigue safety factor due to stress concentration on the corners. Also, it was observed that contact area of spokes to flange affects the total deformation and von-Mises stress distribution. Three dimensional models of the rims were designed with the aid of CATIA V5 and their computational analyses were carried out with ANSYS WORKBENCH software program.