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Prediction of performance and emission characteristics of diesel engine fuelled with waste biomass pyrolysis oil using response surface methodology

机译:利用响应面法预测以废生物质热解油为燃料的柴油机的性能和排放特性

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Advanced third generation biofuels like pyrolysis oil generated from waste biomass paves way for a cleaner and sustainable environment. An experimental-cum-statistical analysis was performed with the aim of determining the optimal engine operating conditions (with respect to compression ratio, load and fuel blend) to enhance the engine operating characteristics (performance and emission) of a diesel engine. Multiple regression models designed by using response surface methodology (RSM) for the output response variables like brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), oxides of carbon (CO&CO2), hydrocarbon (HC), oxides of nitrogen (NOx) and smoke opacity were found to be statistically significant by analysis of variance. Optimization was carried out using desirability approach with a target of maximizing BTE and CO2 simultaneously by minimizing all other responses. From the results, it can be observed that the optimum conditions for bio-oil operation were 18:1 compression ratio, 20% fuel blend and 100% load. The models developed by RSM were validated through confirmatory experiments and found that the models were satisfactory to report the influence of compression ratio, load and bio-oil concentration on the operating characteristics of the diesel engine as the error in prediction is within 5%. (C) 2019 Elsevier Ltd. All rights reserved.
机译:先进的第三代生物燃料,例如由废弃生物质产生的热解油,为清洁和可持续的环境铺平了道路。为了确定最佳的发动机工况(相对于压缩比,负载和燃料混合物),进行了实验和统计分析,以增强柴油机的发动机工况(性能和排放)。通过使用响应曲面方法(RSM)为输出响应变量(如制动比燃料消耗(BSFC),制动热效率(BTE),碳的氧化物(CO&CO2),碳的氧化物(CO&CO2),碳氢化合物(HC),氮的氧化物(NOx)设计的多元回归模型通过方差分析发现烟雾不透明度具有统计学意义。使用期望方法进行了优化,其目标是通过最小化所有其他响应来同时最大化BTE和CO2。从结果可以看出,生物油操作的最佳条件是18:1的压缩比,20%的燃料混合和100%的负荷。通过验证性实验验证了RSM开发的模型,发现该模型能够令人满意地报告压缩比,负载和生物油浓度对柴油机运行特性的影响,因为预测误差在5%以内。 (C)2019 Elsevier Ltd.保留所有权利。

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