The goal of this study is to compare the performance of convolutional windows to that of traditional windows. Convolutional windows are created by convolving the window on its own. These new windows are used to generate a pseudo-LFM signal by combining two stages of piecewise linear frequency functions. The proposed LFM signal was simulated using both traditional and convolutional window functions, and convolutional windows produced higher peak to side lobe level ratio (PSLR) values than traditional windows. The five variables that influence biodiesel yield are reaction time, stirring speed, and temperature. On a small scale, the impact of these variables has been investigated. At optimum conditions of 20% molar ratio, 3% SiO2 catalyst addition, 65oC reaction temperature, 180 min reaction time, and 500 rpm stirring speed, the experimental biodiesel yield is 77 percent. Minitab results are compared to ANN results using a script, both analytically and graphically.
Author(s) Details
Mechanical Engineering, DYPIT, Pune (MS), India and PDEA’S College of Engineering, Manjari, Pune (Affilated to Savitribai Phule Pune University), Pune, India.
R. R. Arakerimath
G H Raisoni College of Engineering and Management, Wagholi, (Affilated to Savitribai Phule Pune University), Pune, India.
View Book :- https://stm.bookpi.org/RDER-V12/article/view/1489
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