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Abstract
The continuous rise in demand, combined with the depletion of the world's fossil fuel reserves, has forced the search for alternative fuels. The biodiesel produced from Roselle is one such indigenous biodiesel with tremendous promise, and its technical ability to operate with compression ignition engines is studied in this work. To characterize the fuel blends, researchers used experimental and empirical approaches while operating at engine loads of 25, 50, 75, and 100%, and with fuel injection timings of 19°, 21°, 23°, 25°, and 27° before top dead center. Results indicate that for 20% blend with the change of injection timing from 19° bTDC to 27° bTDC at full load, brake specific fuel consumption and exhaust gas temperature was increased by 15.84% and 4.60% respectively, while brake thermal efficiency decreases by 4.4%. Also, an 18.89% reduction in smoke, 5.26% increase in CO2, and 12.94% increase in NOx were observed. In addition, an empirical model for full range characterization was created. With an r-squared value of 0.9980 ± 0.0011, the artificial neural network model constructed to characterize all 10 variables was able to predict satisfactorily. Furthermore, substantial correlation among specific variables suggested that empirically reduced models were realistic.
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Details
1 Maulana Azad National Institute of Technology Bhopal, Department of Mechanical Engineering, Bhopal, India (GRID:grid.419487.7) (ISNI:0000 0000 9191 860X)
2 RGM College of Engineering and Technology, School of Mechanical Engineering, Nandyal, India (GRID:grid.419487.7)
3 P. A. College of Engineering (Affiliated To Visvesvaraya Technological University, Belagavi), Department of Mechanical Engineering, Mangaluru, India (GRID:grid.444321.4) (ISNI:0000 0004 0501 2828); Glocal University, Department of Mechanical Engineering, School of Technology, Saharanpur, India (GRID:grid.449790.7) (ISNI:0000 0004 6000 1603)
4 B. S. Abdur Rahman Crescent Institute of Science and Technology, Department of Mechanical Engineering, Vandalur, Chennai, India (GRID:grid.449273.f) (ISNI:0000 0004 7593 9565)
5 Prince Sultan University, Engineering Management Department, College of Engineering, Riyadh, Saudi Arabia (GRID:grid.443351.4) (ISNI:0000 0004 0367 6372)