Effects of different biofuels and their mixtures with diesel fuel on diesel engine performance and exhausts.

In this study, a compression ignition engine that ran on recycled used cooking oil (RUCO), Jatropha curcas (JC), Pongamia Pinnata (PP), and petroleum diesel fuel (PDF) was investigated for its energy, performance, and exhaust emissions. The 20 % by volume RUCO, JC, and PP biofuel mix with PDF is taken. According to the American Society for Testing and Material (ASTM) standard, the blend qualities are evaluated. Viscosity, density, flash point, and heating value have all been tested for the 20 % blend. The outcome indicated that for a 20 % mix, the viscosity, density and flash point were all greater than in the PDF but heat value lower. Because studies have demonstrated that diesel engines can operate on 20 % replacement without any modifications, this study focused on 20 % blend. The engine was tested with loads (Ls) ranging from 0 % to 100 % of its entire capacity while the compression ratios (CRs) was varied. The experimental result demonstrated that the thermal efficiency, as measured by the PDF, was much greater than that of the DRUCO20, DJC20, and DPP20 blends. After the addition of RUCO, JC, and PP to PDF, the temperature of the exhaust gases reduced, and the engine used more gasoline as a result. It was discovered that an engine emissions of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) were lower than those of PDF. Even though it produced a greater amount of carbon dioxide (CO2) emissions, the DRUCO20 was superior to both the DCJ20 and the DPP20.

Optimization of wear behavior of heat-treated Ti-6Al-7Nb biomedical alloy by response surface methodology.

Titanium-based metals are used most often in biomedical implant studies because they have good qualities like being biocompatible, not being poisonous, Osseo-integration, high specific properties, wear resistance, etc. The main goal of this work is to improve the wear resistance of Ti-6Al-7Nb biomedical metal by using a mix of Taguchi, ANOVA, and Grey Relational Analysis. The effect of changeable control process factors like applied load, spinning speed, and time on wear reaction measures like wear rate (WR), coefficient of friction (COF), and frictional force. The optimal combinations of wear rate, COF, and frictional force minimise wear characteristics. The L9 Taguchi orthogonal array was used to plan the experiments, which were done on a pin-on-disc set-up according to ASTM G99. To find the best set of control factors, Taguchi, ANOVA, and Grey relationship analysis were used. The results show that a load of 30 N, a speed of 700 rpm, and a time of 10 min are the best control settings.