期刊
JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING
卷 33, 期 -, 页码 217-230出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jngse.2016.05.026
关键词
Jatropha methyl ester blend; Zinc oxide nano particle; Hydrogen; Artificial neural network; Vibration analysis
资金
- Department of Science and Technology (DST), Government of India (Technology Systems Development) [DST/TSG/AF/2011/125]
In pursuit of environmental friendly alternative fuels for diesel engines, biodiesel is a promising alternative. Efforts are on in utilizing the biodiesel with diesel in Internal Combustion (IC) engines, because of its reduced pollution characteristics. Long-term effects of these biofuels in IC engines have not been explored earnestly. Enduring effects of which are high noise & vibration and irregular & erratic combustion leading to knocking. Few researches on vibration analysis of biodiesel blends have been reported. Hence, an effort is made to study the vibration characteristics of biodiesel blends amidst Zinc Oxide (ZnO) nano particles with hydrogen in dual fuel mode. Initially, experimentation is carried out to record vibration signatures with 100 ppm concentration of ZnO particles of 20 & 40 nm sizes suspended in Jatropha Methyl Ester (JME) biodiesel along with hydrogen as secondary fuel. In order to avoid strenuous experimentation Artificial Neural Network (ANN) model was developed to predict Root Mean Square (RMS) of velocity. ANN predictions are found to be scrupulously matching with the experimental values as manifested by the regression values of 0.97185, 0.98574 & 0.96913 for prediction of RMS velocities in horizontal, vertical & axial directions respectively. It is found that the best fuel blend with least vibration is B30 & B20 with nano particle of size 40 nm for hydrogen flow rates of 0.5, 1.0 & 1.5 l/min. (C) 2016 Elsevier B.V. All rights reserved.
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