Performance, Combustion and Emission Characteristics of a Common Rail Direct Injection Diesel Engine Fueled by Diesel/n-Amyl Alcohol Blends with Exhaust Gas Recirculation Technique

Biofuels are considered as one of the best viable and inexhaustible alternatives to conventional diesel fuel. Alcohols have become very important and popular in the present scenario due to their peculiar fuel properties and production nature. This study examines the effect of n-amyl alcohol and exhaust gas recirculation of 10% and 20% on various engine characteristics of Common Rail Direct Injection (CRDI) compression ignition engine. The proportion of n-amyl alcohol varies from 5% to 25% in 5% step (by volume). The obtained results show that diesel/n-amyl alcohol blends decrease the mean gas temperature and cylinder pressure, which is 1.88% and 4.25% less at 75% load for n-amyl alcohol (25%) with conventional diesel fuel. The duration of combustion has shown a hike of 4.66°CA for 25% n-amyl alcohol (at 75% load) compared to conventional diesel fuel. However, the cumulative heat release rate improved by 12.95% higher for 25% n-amyl alcohol at 75% load, the reason for the same is due to the extended delay in ignition. While n-amyl alcohol was used, the emission of nitrogen oxide emissions decreased considerably. However, the hydrocarbon (HC) (7-9%) and carbon monoxide (CO) (6-8%) emissions are increased due to inferior fuel properties like high latent heat evaporation of n-amyl alcohol. Compared with other blends, n-amyl alcohol (5%) produced results comparable to conventional diesel fuel, which is 3.6% higher in BSFC, 2.37 % higher BTE, and 33.33% higher CO emissions 18.18% more in HC emission, and 17.55% less NOx emission. Without further modification, we can use 25% n-amyl alcohol in the combustion ignition engines. From this evidence, we can summarize that n-amyl alcohol is a biofuel that is both renewable and sustainable, and also it considerably reduces harmful nitrogen oxide emissions. The performance, if needed, can be improved by changing the parameters of the engine.

Artificial Neural Networks and Gompertz Functions for Modelling and Prediction of Solvents Produced by the S. cerevisiae Safale S04 Yeast

The present work aims to develop a mathematical model, based on Gompertz equations and ANNs to predict the concentration of four solvent compounds (isobutanol, ethyl acetate, amyl alcohol and n-propanol) produced by the yeasts S. cerevisiae, Safale S04, using only the fermentation temperature as input data. A beer wort was made, daily samples were taken and analysed by GC-FID. The database was grouped into five datasets of fermentation at different setpoint temperatures (15.0, 16.5, 18.0, 19.0 and 21.0 °C). With these data, the Gompertz models were parameterized, and new virtual datasets were used to train the ANNs. The coefficient of determination (R2) and p-value were used to compare the results. The ANNs, trained with the virtual data generated with the Gompertz functions, were the models with the highest R2 values (0.939 to 0.996), showing that the proposed methodology constitutes a useful tool to improve the quality (flavour and aroma) of beers through temperature control.

Biosynthesis of Amyl Alcohol from Scenedesmus quadricauda Microalgae for Light Commercial Vehicle CI Engine using Prediction Models

Third generation feedstocks and its constituent biofuels have shown promising results in the light of sustainable production and as a feasible fuel source for internal combustion engines. Hence, in this study, a third generation microalgae feedstock (scenedesmus quadricauda) biomass was cultivated sustainably using an in-situ tubular photo bioreactor and raceway pond to synthesize quintet carbon chained amyl alcohol using Ehrlich biosynthetic pathway. On analyzing the synthesized amyl alcohol, a homogenous mixture of a 20 % (vol/vol) amyl alcohol-diesel blend showed similarities with conventional diesel in their physio-chemical properties. This potential fuel source was analyzed though systematic experimentation at maximum throttle position condition in a light commercial vehicle compression ignition engine. The conducted experiments were directed by Response Surface Methodology coupled with Central Composite Design which delivered a set of influential and interactive responses on engine testing. At optimal operating condition, 0.7% rise in brake thermal efficiency and an increased specific fuel consumption of 5.6% is reported due to the lower heating value of the biofuel. Furthermore, a 55.8% and 5.4% drop in smoke and carbon monoxide emissions is observed. However, oxides of nitrogen emission increases by 31.7% for biofuel operation as a trade-off for the improved combustion characteristics achieved.