Performance and Emission Analysis of Biodiesel Blends in a Low Heat Rejection Engine with an Antioxidant Additive: An Experimental Study.

The rapid depletion of crude oil and environmental degradation necessitate the search for alternative fuel sources for internal combustion engines. Biodiesel is a promising alternative fuel for compression ignition (CI) engines due to its heat content and combustion properties. Biodiesel blends are used in various vehicles and equipment, such as cars, trucks, buses, off-road vehicles, and oil furnaces. Biodiesel can reduce emissions from CI engines by up to 75% and improve engine durability due to its high lubricity. However, biodiesel has some drawbacks, including a performance reduction and increased nitrogen oxide emissions. Therefore, this study aims to investigate using environmentally available biodiesel in a low-heat rejection engine and an antioxidant additive to enhance the performance and reduce nitrogen oxide emissions. India currently has several biodiesel sources, including mango seed oil, mahua oil, and pongamia oil, which can be effectively utilized in CI engines by adding l-ascorbic acid. The experimental work involves a single-cylinder 4-stroke water-cooled direct injection CI engine with a power output of 5.2 kW. The engine's cylinder head, piston head, and valves are coated with lanthanum oxide using the plasma spray coating technique, with a thickness of 0.5 mm. The coated and uncoated engines are tested with different proportions of mahua oil, mango seed oil, and pongamia oil. The results show that the engine's performance is significantly improved compared to the baseline engine at all loads. Additionally, these biodiesels exhibit a notable reduction in nitrogen oxide emissions when combined with l-ascorbic acid.

Effect of Infill Patterns with Machine Learning Techniques on the Tensile Properties of Polylactic Acid-Based Ceramic Materials with Fused Filament Fabrication.

The field of additive manufacturing is quickly evolving from prototyping to manufacturing. Researchers are looking for the best parameters to boost mechanical strength as the demand for three-dimensional (3D) printers grows. The goal of this research is to find the best infill pattern settings for a polylactic acid (PLA)-based ceramic material with a universal testing machine; the impact of significant printing considerations was investigated. An X-ray diffractometer and energy-dispersive X-ray spectroscopy with an attachment of scanning electron microscopy were used to investigate the crystalline structure and microstructure of PLA-based ceramic materials. Tensile testing of PLA-based ceramics using a dog bone specimen was printed with various patterns, as per ASTM D638-10. The cross pattern had a high strength of 16.944 MPa, while the tri-hexagon had a peak intensity of 16.108 MPa. Cross3D and cubic subdivisions have values of 4.802 and 4.803 MPa, respectively. Incorporating the machine learning concepts in this context is to predict the optimal infill pattern for robust strength and other mechanical properties of the PLA-based ceramic model. It helps to rally the precision and efficacy of the procedure by automating the job that would entail substantial physical effort. Implementing the machine learning technique to this work produced the output as cross and tri-hexagon are the efficient ones out of the 13 patterns compared.

Experimental Investigation for Determining an Ideal Algal Biodiesel-Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology.

The ongoing depletion of the world's fossil fuel sources and environmental damage has compelled the quest for alternative energy. Excellent characteristics of biodiesel include its renewable nature, safety, absence of sulfur, environmental advantages, and biodegradability, which can eradicate the above problems. In this study, algal oil was characterized to obtain the fatty acid profile, and the free fatty acid value of algal oil suggested a two-step process of esterification and transesterification for efficient biodiesel production. The performance and emission results of biodiesel and its blends (B10, B20, and B30) were investigated in a constant speed, single-cylinder, 4-stroke, 3.5 kW compression ignition engine at different loads for arriving at an appropriate fuel blend ratio. The response surface methodology technique is used to predict the ideal composition of microalgae-diesel using the experimental data with due weightage for the optimization criterion. The predicted blend ratio of B25 was tested on the engine and authenticated. The findings recorded an improvement in brake thermal efficiency to 31.42% and reduction in brake specific energy consumption to 9.82 MJ/kW h, unburned hydrocarbon to 85 ppm, carbon monoxide to 0.164% v/v, carbon dioxide to 4.115% v/v, nitrogen oxides to 691 ppm, and smoke opacity to 16.93%.

In vitro antioxidant studies of Dioscorea esculenta (Lour). Burkill

Objective: To evaluate the total phenolic, flavonoid contents and in vitro antioxidant activity of methanol extract of Dioscorea esculenta (Lour). Burkill. Methods: Total phenolic content was estimated using the Folin Ciocalteu method. The flavonoid content was determined using aluminium chloride. In vitro antioxidant activities and reducing power capacity were determined using standard methods. Results: Total phenolic content in methanol extract of Dioscorea esculenta was found to be 0.79g/100g and flavonoids content was found to be 0.26 g/100g. The extract was screened for its potential antioxidant activities using tests such as DPPH radical scavenging activity, hydroxyl radical scavenging activity, superoxide radical scavenging activity, ABTS radical cation scavenging activity and reducing power activity. Conclusions: The present studies confirm the methanol extracts have potential in vitro antioxidant activity. The phytochemical phenols and flavonoids could be the reason for its antioxidant activity.