×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerThis study establishes a risk aware, multi objective methodology to select diesel plastic fuel α-terpineol blends that deliver robust engine performance across operating loads in a common rail direct injection diesel engine. Heterogeneous responses brake thermal efficiency, brake specific fuel consumption, oxides of nitrogen, carbon monoxide, hydrocarbons, smoke, and exhaust gas temperature are mapped to a unitless desirability scale and aggregated by load. Conditional Value at Risk across loads then prioritizes worst case behavior. By Conditional Value at Risk at level 0.20, the ranking is: diesel 0.242, diesel plastic fuel with 15% α-terpineol 0.197, 10% α-terpineol is 0.177, 5% α-terpineol is 0.157, diesel plastic fuel is 0.141, waste plastic fuel is 0.081. Relative to neat diesel plastic fuel, worst-case performance improves by 11% at 5% α-terpineol, 26% at 10% α-terpineol, and 40% at 15% α-terpineol, with the 100% load consistently governing the tail. Average brake specific fuel consumption decreases from 0.4553 to 0.4217 kg/kWh at 15% α-terpineol, average exhaust gas temperature falls from 321.4 to 293.0°C. Duty map mean oxides of nitrogen reduce from 512 to 474 ppm, hydrocarbons fall from 42.67 to 35.73 ppm. At full load, carbon monoxide declines from 0.52 to 0.46 %vol., and smoke opacity decreases from 52.28 to 49.71%. Within the tested window, 15% α-terpineol in diesel plastic fuel is the risk aware first choice, with 10% α-terpineol a near optimal alternative. The methodology remains stable under risk aversion and weighting changes at high-load calibration.
The consequence of mixing pure ethanol with gasoline on the pollution and performance of SI engine are investigated experimentally in the existent study. The SI engine that employed in the experiment is a single cylinder four stroke. Analysis is carried out for engine operation parameter, CO2, CO and unburned HC productions. The measurements are recorded for several engine speeds from 1500 – 3000 rpm with load and ethanol addition of (0E, 10E, 20E, 30E, 40E, 50E,). The results displayed increasing in brake power, and brake thermal efficiency while the brake specific fuel consumption decreases when the ethanol- gasoline blends fuel increases. Also it was found that CO, HC, and CO2 concentrations decrease when the ethanol- gasoline increases. The best results obtained in the study is for the blend of E-50.
Road transport undeniably constitutes the predominant mechanism for facilitating the transportation of both goods and individuals on a global scale, serving as an essential backbone for economic and social interactions across diverse regions and cultures. The noticeable decrease in the flow of vehicles, which can be attributed to a plethora of internal and external factors, with a particular emphasis on the phenomenon of congestion, has profound implications that significantly influence fuel consumption rates, contribute to pollution associated with emissions, adversely affect the health and well-being of bystanders, and culminate in a considerable loss of time for individuals navigating these congested environments. In light of their elevated population densities coupled with their classification as emerging economies, South Asian countries find themselves necessitated to implement automated systems for the critical processes of predicting, identifying, and effectively addressing the challenges posed by road traffic congestion in order to enhance urban mobility and overall transport efficiency. This thorough research carefully explores the various techniques that have been utilized to recognize traffic congestion, presenting an extensive assessment of their individual strengths and weaknesses, thus offering insightful observations about the existing situation in this field of study. The examination of the diverse approaches and advanced technologies that have been utilized for the operation of lane-less roadways have been conducted, revealing substantial potential for further innovations that could greatly assist future researchers in their endeavors to enhance traffic management and improve roadway safety and efficiency.