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Many factors affect the vehicular fuel consumption rate. The most significant traffic-related ones are speed, number of stops, speed noise, and acceleration noise (acceleration standard deviation). Fuel consumption models for both urban and highway traffic are used to evaluate the effect of these factors. Previous literature shows the speed and the acceleration of vehicles as well as the aerodynamic effects are the most commonly used variables in the highway fuel consumption mo dels. However, most existing models are based on the average or cruising speed and the effect of speed variation is by-and-large ignored. Incorporating the speed noise as a variable in the prediction models seems impractical because measuring it is cumbersome. However, knowing the relation between speed and speed noise may allow including the effect of speed noise in the model indirectly. To that end, this study examines the relation between speed and speed noise. The resulting mathematical relation is used to incorporate the speed noise effects in the fuel consumption model.
This paper presents an experimental investigation focused on identifying the effects of cutting conditions and tool construction on the surface roughness and natural frequency in turning of AISI1045 steel. Machining experiments were carried out at the lathe using carbide cutting insert coated with TiC and two forms of cutting tools made of AISI 5140 steel. Three levels for spindle speed, depth of cut, feed rate and tool overhang were chosen as cutting variables. The Taguchi method L9 orthogonal array was applied to design of experiment. By the help of signal-to-noise ratio and analysis of variance, it was concluded that spindle speed has the significant effect on the surface roughness, while tool overhang is the dominant factor affecting natural frequency for both cutting tools. In addition, the optimum cutting conditions for surface roughness and natural frequency were found at different levels. Finally, confirmation experiments were conducted to verify the effectiveness and efficiency of the Taguchi method in optimizing the cutting parameters for surface roughness and natural frequency.