:Modeling of biodiesel production: Performance comparison of Box–Behnken, face central composite and full factorial design论文

:Modeling of biodiesel production: Performance comparison of Box–Behnken, face central composite and full factorial design论文

本文主要研究内容

作者(2019)在《Modeling of biodiesel production: Performance comparison of Box–Behnken, face central composite and full factorial design》一文中研究指出:The performances of the response surface methodology(RSM) in connection with the Box–Behnken, face central composite or full factorial design(BBD, FCCD or FFD, respectively) were compared for the use in modeling of the NaOH-catalyzed sunflower oil ethanolysis. The influence of temperature, catalyst loading, and ethanol-to-oil molar ratio(EOMR) on fatty acid ethyl esters(FAEE) content was evaluated. All three multivariate strategies were efficient in the statistical modeling and optimization of the influential process variables but BBD and FCCD realization involved less number of experiments, generating smaller costs, requiring less work and consuming shorter time than the corresponding FFD. All three designs resulted in the same optimal catalyst loading(1.25% of oil) and EOMR(12:1). The reduced two-factorinteraction(2 FI) models based on the BBD and FCCD defined a range of optimal reaction temperature(25 °C–75 °C) and 25 °C, respectively while the same model based on the 33 FFD appointed 75 °C. The predicted FAEE content of about 97%–98.0% was close to the experimentally obtained FAEE content of about 97.0%–97.6% under the optimal reaction conditions. Therefore, the simpler BBD or FCCD might successfully be applied for statistical modeling of biodiesel production processes instead of the more extensive,more laborious and more expensive FFD.

Abstract

The performances of the response surface methodology(RSM) in connection with the Box–Behnken, face central composite or full factorial design(BBD, FCCD or FFD, respectively) were compared for the use in modeling of the NaOH-catalyzed sunflower oil ethanolysis. The influence of temperature, catalyst loading, and ethanol-to-oil molar ratio(EOMR) on fatty acid ethyl esters(FAEE) content was evaluated. All three multivariate strategies were efficient in the statistical modeling and optimization of the influential process variables but BBD and FCCD realization involved less number of experiments, generating smaller costs, requiring less work and consuming shorter time than the corresponding FFD. All three designs resulted in the same optimal catalyst loading(1.25% of oil) and EOMR(12:1). The reduced two-factorinteraction(2 FI) models based on the BBD and FCCD defined a range of optimal reaction temperature(25 °C–75 °C) and 25 °C, respectively while the same model based on the 33 FFD appointed 75 °C. The predicted FAEE content of about 97%–98.0% was close to the experimentally obtained FAEE content of about 97.0%–97.6% under the optimal reaction conditions. Therefore, the simpler BBD or FCCD might successfully be applied for statistical modeling of biodiesel production processes instead of the more extensive,more laborious and more expensive FFD.

论文参考文献

  • [1].Artificial Neural Network and Full Factorial Design Assisted AT-MRAM on Fe Oxides, Organic Materials, and Fe/Mn Oxides in Surficial Sediments[J]. GAO Qian, WANG Zhi-zeng, WANG Qian, LI Shan-shan and LI Yu* Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing 102206, P. R. China.  Chemical Research in Chinese Universities.2011(06)
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