Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization

Arridina Susan Silitonga, Teuku Meurah Indra Mahlia, Abd Halim Shamsuddin, Hwai Chyuan Ong, Jassinnee Milano, Fitranto Kusumo, Abdi Hanra Sebayang, Surya Dharma, Husin Ibrahim, Hazlina Husin, M. Mofijur and S. M. Ashrafur Rahman
Additional contact information
Arridina Susan Silitonga: Department of Mechanical Engineering, Politeknik Negeri Medan, Medan 20155, Indonesia
Teuku Meurah Indra Mahlia: School of Information, Systems and Modelling, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia
Abd Halim Shamsuddin: Institute of Sustainable Energy, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia
Hwai Chyuan Ong: School of Information, Systems and Modelling, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia
Jassinnee Milano: Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
Fitranto Kusumo: Institute of Sustainable Energy, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia
Abdi Hanra Sebayang: Department of Mechanical Engineering, Politeknik Negeri Medan, Medan 20155, Indonesia
Surya Dharma: Department of Mechanical Engineering, Politeknik Negeri Medan, Medan 20155, Indonesia
Husin Ibrahim: Department of Mechanical Engineering, Politeknik Negeri Medan, Medan 20155, Indonesia
Hazlina Husin: Department of Petroleum Engineering, Faculty of Engineering, Universiti Teknologi Petronas, Persiaran UTP, Seri Iskandar 32610, Perak, Malaysia
M. Mofijur: School of Information, Systems and Modelling, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia
S. M. Ashrafur Rahman: Biofuel Engine Research Facility (BERF), Queensland University of Technology, Brisbane, QLD 4000, Australia

Energies, 2019, vol. 12, issue 20, 1-21

Abstract: Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) esterification and (2) transesterification. The parameters of esterification and transesterification processes were optimized to minimize the acid value and maximize the C. manghas biodiesel yield, respectively. There was excellent agreement between the average experimental values and those predicted by the artificial neural network models, indicating their reliability. These models will be useful to predict the optimum process parameters, reducing the trial and error of conventional experimentation. The kinetic study was conducted to understand the mechanism of the transesterification process and, lastly, the model could measure the physicochemical properties of the C. manghas biodiesel.

Keywords: Cerbera manghas oil; biodiesel; artificial neural networks; ant colony optimization; kinetic study (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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