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Biodiesel production from castor oil: ANN modeling and kinetic parameter estimation

机译:来自蓖麻油的生物柴油生产:ANN建模和动力学参数估计

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This research work concerns with the transesterification of castor oil with methanol to form biodiesel. As the free fatty acid content in castor oil is more than 1%, an acid catalyst namely, H2SO4 has been used for esterification. The experimental conditions were determined using central composite design method and the experiments were conducted in a 2?L working volume fully controlled reactor. The input conditions namely, catalyst concentration, methanol to oil molar ratio and temperature were varied, and % fatty acid methyl ester (FAME) content was determined. Based upon the experimental data, an ANN model has been developed which is used to predict %FAME yield for a given set of input conditions. The experimental data and the data predicted by the ANN model have been used to estimate the rate constants of a kinetic model. The ANN model predicts the % FAME yield within ±8% deviation, and the developed kinetic model shows successfully the effect of methanol to oil molar ratio on % FAME yield at 60?°C and 3% (v/v) catalyst loading.
机译:这项研究与蓖麻油酯交换与甲醇形成生物柴油的临疑。随着蓖麻油中的游离脂肪酸含量大于1%,即酸催化剂即,H2SO4已被用于酯化。使用中央复合设计方法测定实验条件,实验在2〜L工作体积完全控制的反应器中进行。输入条件即,催化剂浓度,甲醇与油摩尔比和温度变化,并测定%脂肪酸甲酯(CAME)含量。基于实验数据,已经开发了ANN模型,其用于预测给定的一组输入条件的%名称产量。 ANN模型预测的实验数据和数据已经用于估计动力学模型的速率常数。 ANN模型预测±8%偏差范围内的%名称产量,并且发育的动力学模型成功地成功地将甲醇与60℃和3%(v / v)催化剂负载的%dame产率的影响。

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