A central composite face-centered design (CCFD) was employed to examine the optimal conditions for the compression ratio of the Sardine Fish Oil Methyl Ester (SFOME) blend to the Thermal cracked Cashew Shell Nut Liquid T-CSNL blend by simultaneously considering the brake thermal efficiency (BTE), the brake specific fuel consumption (BSFC), carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO x ) emissions as response variables. The experimental results obtained were analyzed with the help of Design Expert software, and output response predictions were fitted with a polynomial quadratic model of the second degree. The maximum overall desirability obtained for the entire model was 0.7506 with a compression ratio of 19.31 and blend ratios of 20% for SFOME and 15.72% for T-CSNL by volume proportion. Under optimum conditions, it was found that the predicted and experimental results were very similar, and it can be concluded that the quadratic model of second-order can precisely predict the performance and emission characteristics of engines.Energies 2018, 11, 3508 2 of 13 largely responsible for the above-mentioned problems which can be decreased by transesterification, pyrolysis, emulsification, preheating, and blending with diesel.Transesterification is the reaction between a triglyceride and alcohol in the existence of a catalyst, resulting in fatty acid esters and an alcohol [6]. The most commonly used alcohols for the production of biodiesels in transesterification reactions are methanol, ethanol, propanol, and butanol. However, the most frequently utilized alcohols are methanol and ethanol [7]. Some of the commonly used catalysts to increase the reaction rate are acids, bases, or enzymes. The raw materials used for biodiesel production include edible vegetable oils, such as linseed, soybean, hazelnut, rapeseed canola, and coconut oil; non-edible vegetable oils, such as pongamiapinnata, azadirachtaindica, Moringaoleifera, and Crotonmegalocarpus; and animal fats and cooking oil waste from food processing units, restaurants, or domestic kitchens [8]. In India, the cost of the raw oil used to produce biodiesels is an important factor in the price of biodiesel and determines the effectiveness of petroleum-products derived from crude oil. Moreover, the use of oil from edible oil-bearing plants to produce biodiesel in India is not feasible because of the large gap between demand and supply that restricts the use of edible oil as feedstock for biodiesel production [9]. In this context, the search for a non-edible feedstock as a cheap, environmentally friendly, and stable raw oil source has attracted great attention. Many researchers have put effort into minimizing the costs incurred during the production of oil feedstock, and hence, the exploration of new techniques to curtail the cost of biodiesels has attracted much interest in current research [10,11]. In this context the low cost, low value Thermally cracked Cashew Shell Nut Liquid (TCSNL) oil is considered an alternate fuel source. Over the past years, ma...
The main purpose of the experiment is to investigate the performance and emission characteristics of a hydrous methanol (85% methanol and 15% water) fueled homogeneous charge compression ignition (HCCI) engine through various spark timings (SPT) (32°, 34°, 36°, 38° and 40° before Top Dead Centre). In this study a spark plug is used for assisting auto‐ignition. Experimental investigation reveals that the brake thermal efficiency (BTE) of an HCCI engine increases when the SPT is increased and a maximum BTE of 28.5% was obtained for 40°SPT. Emission analysis reveals a significant decrease in nitrogen oxides (NOx) as there are slightly higher emissions of hydrocarbon (HC) and carbon monoxide (CO). An artificial neural network (ANN) was developed with brake mean effective pressure (BMEP), SPT, and energy share as the input data and BTE, NOx, HC, CO, and rate of pressure rise as output data. In this prediction technique, about 80% of experimental data obtained were used in training and 20% of data were used to test the model developed. The performance in the developed ANN models was compared with experimental data, and statistically evaluated; they are seen to have good agreement. © 2015 Society of Chemical Industry and John Wiley & Sons, Ltd
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