期刊
RENEWABLE ENERGY
卷 76, 期 -, 页码 408-417出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2014.11.049
关键词
Shea butter; Biodiesel; Transesterification; Artificial neural network; Response surface methodology; Optimization
This work investigated the potential of shea butter oil (SBO) as feedstock for synthesis of biodiesel. Due to high free fatty acid (FFA) of SBO used, response surface methodology (RSM) was employed to model and optimize the pretreatment step while its conversion to biodiesel was modeled and optimized using RSM and artificial neural network (ANN). The acid value of the SBO was reduced to 1.19 mg KOH/g with oil/ methanol molar ratio of 3.3, H2SO4 of 0.15 v/v, time of 60 min and temperature of 45 degrees C. Optimum values predicted for the transesterification reaction by RSM were temperature of 90 degrees C, KOH of 0.6 w/v, oil/ methanol molar ratio of 3.5, and time of 30 mm with actual shea butter oil biodiesel (SBOB) yield of 99.65% (w/w). ANN combined with generic algorithm gave the optimal condition as temperature of 82 degrees C, KOH of 0.40 w/v, oil/methanol molar ratio of 2.62 and time of 30 min with actual SBOB yield of 99.94% (w/w). Coefficient of determination (R-2) and absolute average deviation (AAD) of the models were 0.9923, 0.83% (RSM) and 0.9991, 0.15% (ANN), which demonstrated that ANN model was more efficient than RSM model. Properties of SBOB produced were within biodiesel standard specifications. (C) 2014 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据