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

Silitonga, Arridina Susan and Mahlia, Teuku Meurah Indra and Shamsuddin, Abd Halim and Ong, Hwai Chyuan and Milano, Jassinnee and Kusumo, Fitranto and Sebayang, Abdi Hanra and Dharma, Surya and Ibrahim, Husin and Husin, Hazlina and Mofijur, M. and Rahman, S.M. Ashrafur (2019) Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization. Energies, 12 (20). p. 3811. ISSN 1996-1073, DOI https://doi.org/10.3390/en12203811.

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Official URL: https://doi.org/10.3390/en12203811


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. © 2019 by the authors.

Item Type: Article
Funders: Direktorat Jenderal Penguatan Riset dan Pengembangan Kementerian Riset, Teknologi dan Pendidikan Tinggi Republik Indonesia, (Grant no. 147/SP2H/LT/DRPM/2019) and Politeknik Negeri Medan, Medan, Indonesia, AAIBE Chair of Renewable Energy (Grant no: 201801 KETTHA), University of Malaya, Kuala Lumpur Malaysia, for funding this work under their RU Geran—Faculty Program (GPF021A-2019), Centre for Advanced Modeling and Geospatial Information System (CAMGIS), University of Technology Sydney, Australia under Grants 321740.2232397
Uncontrolled Keywords: Cerbera manghas oil; biodiesel; artificial neural networks; ant colony optimization; kinetic study
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 14 Jan 2020 05:05
Last Modified: 14 Jan 2020 05:05
URI: http://eprints.um.edu.my/id/eprint/23432

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