Considering the importance of alternative fuels in IC engines for environment safety, compressed natural gas has been extensively employed in SI engines. However, scarce efforts have been made to investigate the effect of compressed natural gas on engine lubricant oil for a long duration. In this regard, a comprehensive analysis has been made on the engine performance, emissions, and lubricant oil conditions using gasoline ( G)92 and compressed natural gas at different operating conditions using reliable sampling methods. The key parameters of the engine performance like brake power and brake-specific energy consumption were investigated at 80% throttle opening within 1500–4500 range of r/min. For the sake of emission tests, speed was varied uniformly by varying the load at a constant throttle. Furthermore, the engine was run at high and low loads for lubricant oil comparison. Although compressed natural gas showed a decrease in brake-specific energy consumption (7.94%) and emissions content, ( G)92 performed relatively better in the case of brake power (39.93% increase). Moreover, a significant improvement was observed for wear debris, lubricant oil physiochemical characteristics, and additives depletion in the case of compressed natural gas than those of ( G)92. The contents of metallic particles were decreased by 23.58%, 36.25%, 42.42%, and 66.67% for iron, aluminum, copper, and lead, respectively, for compressed natural gas.
In present study a turbocharged, medium duty compression ignition engine was alternatively fuelled with biodiesel to investigate the changes in particulate matter composition, relative to that taken with diesel fuel. The engine was operated on an AC electrical dynamometer in accordance with an 8-mode, steady-state cycle. The numbers of particles were estimated through electrical low pressure impactor, while sulfates and trace metals were analyzed by ion chromatography and inductively coupled plasma-atomic emission spectroscopy, respectively. Nitric oxides and nitrogen dioxides were measured separately using SEMTECH-DS. Experimental results revealed that, on account of elevated ratios of nitrogen dioxide to nitrogen oxides, mean accumulation mode particles were 42 % lower with biodiesel. On the other hand, nuclei mode particles were higher with biodiesel, owing to heterogeneous nucleation and accounting for an increase in sulfate emissions up to 8 % with biodiesel as compared to diesel. On the average, trace metal emissions were significantly reduced showing 65-85.4 % reduction rates with biodiesel, relative to its counterpart. Further to this, individual congeners such as iron, calcium, and sodium were the predominant elements of the trace metals emitted from engine. The mean relative decrease in iron and calcium was 89-97.8 and 77.6-87 %, respectively, while the relative rise in sodium was in the range of 29-46 % with biodiesel. Further, elements such as zinc, chromium, and aluminum showed substantial abatement, whereas potassium, magnesium, and manganese exhibited irregular trends on account of variable engine loads and speeds during the various modes of cycle.
Stainless steel (SS 304) is commonly employed in industrial applications due to its considerable corrosion resistance, thermal resistance, and ductility. Most of its intended applications require the formation of complex profiles, which justify the use of wire electrical discharge machining (WEDM). However, its high thermal resistance imposes a limitation on acquiring adequate surface topography because of the high surface tension of the melt pool, which leads to the formation of spherical modules; ultimately, this compromises the surface quality. Furthermore, the stochastic nature of the process makes it difficult to optimize its performance, especially if more than one conflicting response is involved, such as high cutting speed with low surface roughness and kerf width. Therefore, this study aimed to comprehensively investigate the interaction of SS 304 and WEDM, with a prior focus on simultaneously optimizing all the conflicting responses using the Taguchi-based grey relational approach. Analysis of variance (ANOVA) revealed that the current was the most significant parameter for cutting speed and kerf, whereas roughness, voltage (45%), drum speed (25.8%), and nozzle offset distance (~21%) were major contributing factors. SEM micrographs showed that optimal settings not only ensured simultaneous optimization of the conflicting responses but also reduced the number and size of spherical modules.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.