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首页> 外文期刊>Frontiers in energy >Development of a combined approach for improvement and optimization of karanja biodiesel using response surface methodology and genetic algorithm
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Development of a combined approach for improvement and optimization of karanja biodiesel using response surface methodology and genetic algorithm

机译:使用响应面法和遗传算法开发改进和优化卡拉尼生物柴油的组合方法

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摘要

This paper described the production of karanja biodiesel using response surface methodology (RSM) and genetic algorithm (GA). The optimum combination of reaction variables were analyzed for maximizing the biodiesel yield. The yield obtained by the RSM was 65% whereas the predicted value was 70%. The mathematical regression model proposed from the RSM was coupled with the GA. By using this technique, 90% of the yield was obtained at a molar ratio of 38, a reaction time of 8 hours, a reaction temperature of 40 ℃, a catalyst concentration of 2% oil, and a mixing speed of 707r/min. The yield produced was closer to the predicted value of 94.2093%. Hence, 25% of the improvement in the biodiesel yield was reported. Moreover the different properties of karanja biodiesel were found closer to the American Society for Testing & Materials (ASTM) standard of biodiesel.
机译:本文介绍了使用响应面法(RSM)和遗传算法(GA)来生产karanja生物柴油。分析了反应变量的最佳组合以最大化生物柴油的产率。通过RSM获得的产率为65%,而预测值为70%。 RSM提出的数学回归模型与GA结合使用。通过使用该技术,以38的摩尔比,8小时的反应时间,40℃的反应温度,2%的油催化剂浓度和707r / min的混合速度获得了90%的收率。产生的产率更接近预期值94.2093%。因此,据报道生物柴油产量提高了25%。此外,发现karanja生物柴油的不同特性更接近美国生物材料测试与材料协会(ASTM)标准。

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