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This paper deals with the experimental investigation of CI engine run with multiple biodiesels –diesel blended and neat diesel fuels along with the energy-exergy analysis to evaluate quantitative and qualitative data for determining energy and exergy efficiencies, losses and exergy destruction. Second-generation biodiesels are utilised to conduct experiments on a DICI engine with constant speed and full throttle condition at a compression ratio of 17.5:1. Energy analysis is based on experimental data, and exergy analysis is performed with the help of derived formula using chemical and molecular structures. Variation in the performance, combustion, and emission parameters for B0, B10, and B20 blends reveals that BTE, AFR, η(mech.), η(vol.), CP, and CO decreases with the increase in BSEC, EGT, MGT, RPR, NHR, CO2, HC, and NOx. Energy-exergy analysis shows that the combustion and exergetic efficiencies are maximum for the B20 blend (+87.73%) and (+52.04%) at 2.5 kW and 3.3 kW BPs. Exergy destructed is observed to be three-fifth of total available exergy. Half of the heat supplied is carried away by cooling water while one-third of heat is converted into brake power, and the remaining heat is lost in exhaust gases and unaccounted losses.

Biodiesel is double sided Sword. Due to depletion of fossil diesel, the Biodiesel have taken same position in the fossil fuel category. That's why now a day the world is taking step towards the biodiesel because the depletion of fossil diesel. Biodiesel is basically Fatty Acid methyl ester based fuel, a long chain of triglycerides and the alcohol in the presence of catalyst forms ethyl esters and the glycerol that process is known as Transesterification, if the free fatty acid content percentage in the oil is more than 2.5 % then the process by which the oil is converted to ethyl esters is known as Esterification followed by Transesterification. In this study we mostly concentrate on the physio -chemical properties; The Physio -chemical properties like Density, Kinematic Viscosity, Flash Point, Cetane Number, are having statistical correlations with the Gross Calorific Value of Karanja Oil Methyl Ester (KOME). We have also shown in the paper, the individual properties how much percent statistical correlation have with the gross calorific value, we have calculated it by Least square Approximation of Linear Regression.

This research paper focuses on the modeling of total cases due to COVID-19 and the critical assessment of socioeconomic impact on India. The data set considered for the present analysis is from December 31, 2019 to May 16, 2020 for training and testing of developed regression model. Least-square approximation of linear regression technique is applied to estimate the total cases of COVID-19. Three variables, viz. daily new cases, total deaths and daily new deaths, were considered for development of correlations. In the present study, seven correlations are developed as a function of single variable, two variables and three variables with accuracy (R 2 ) ranging from 85.71 to 99.95%. The paper also highlights the socioeconomic impact of COVID 19 on different sector, challenges and remedies for improving the GDP of the country.

Most promising alternative source available for fossil diesel in India is the Pongamia pinnata biodiesel (Karanja biodiesel in the Indian context). The characterization of biodiesel plays an important role in engine emission and performance. Due to oxygenation the biodiesel has low higher heating value than fossil diesel hence it is necessary to study the effect of different physio-chemical properties on higher heating value. Experimentations were conducted on 11 samples on the basis of Volume % for Pongamia Pinnata biodiesel and diesel blends in the step of 10 varying from 0% (Fossil diesel) to 100% (Pongamia pinnata biodiesel). A retrospective investigation is conducted for characterization of biodiesels and different physio-chemical properties are correlated as a function of Higher Heating Value (HHV). By the traditional statistical technique of regression analysis the correlations can predict the HHV values with the accuracy of R2=0.9907 and uncertainty of ±6.19%. HHVs obtained by performing experiments and by predicted correlations are compared with the correlations available in open literature. The study reveals that the properties of kinematic viscosity and density have a strong correlation with HHV as compared to cetane number and flash point.