LAPSE:2023.28978
Published Article

LAPSE:2023.28978
Modeling and Optimization of Microwave-Based Bio-Jet Fuel from Coconut Oil: Investigation of Response Surface Methodology (RSM) and Artificial Neural Network Methodology (ANN)
April 12, 2023
Abstract
In this study, coconut oils have been transesterified with ethanol using microwave technology. The product obtained (biodiesel and FAEE) was then fractional distillated under vacuum to collect bio-kerosene or bio-jet fuel, which is a renewable fuel to operate a gas turbine engine. This process was modeled using RSM and ANN for optimization purposes. The developed models were proved to be reliable and accurate through different statistical tests and the results showed that ANN modeling was better than RSM. Based on the study, the optimum bio-jet fuel production yield of 74.45 wt% could be achieved with an ethanol−oil molar ratio of 9.25:1 under microwave irradiation with a power of 163.69 W for 12.66 min. This predicted value was obtained from the ANN model that has been optimized with ACO. Besides that, the sensitivity analysis indicated that microwave power offers a dominant impact on the results, followed by the reaction time and lastly ethanol−oil molar ratio. The properties of the bio-jet fuel obtained in this work was also measured and compared with American Society for Testing and Materials (ASTM) D1655 standard.
In this study, coconut oils have been transesterified with ethanol using microwave technology. The product obtained (biodiesel and FAEE) was then fractional distillated under vacuum to collect bio-kerosene or bio-jet fuel, which is a renewable fuel to operate a gas turbine engine. This process was modeled using RSM and ANN for optimization purposes. The developed models were proved to be reliable and accurate through different statistical tests and the results showed that ANN modeling was better than RSM. Based on the study, the optimum bio-jet fuel production yield of 74.45 wt% could be achieved with an ethanol−oil molar ratio of 9.25:1 under microwave irradiation with a power of 163.69 W for 12.66 min. This predicted value was obtained from the ANN model that has been optimized with ACO. Besides that, the sensitivity analysis indicated that microwave power offers a dominant impact on the results, followed by the reaction time and lastly ethanol−oil molar ratio. The properties of the bio-jet fuel obtained in this work was also measured and compared with American Society for Testing and Materials (ASTM) D1655 standard.
Record ID
Keywords
ANN, bio-jet fuel, coconut oil, microwave-assisted transesterification, Optimization, RSM
Suggested Citation
Ong MY, Nomanbhay S, Kusumo F, Raja Shahruzzaman RMH, Shamsuddin AH. Modeling and Optimization of Microwave-Based Bio-Jet Fuel from Coconut Oil: Investigation of Response Surface Methodology (RSM) and Artificial Neural Network Methodology (ANN). (2023). LAPSE:2023.28978
Author Affiliations
Ong MY: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia [ORCID]
Nomanbhay S: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia
Kusumo F: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia [ORCID]
Raja Shahruzzaman RMH: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia
Shamsuddin AH: AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia
Nomanbhay S: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia
Kusumo F: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia [ORCID]
Raja Shahruzzaman RMH: Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia; AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia
Shamsuddin AH: AAIBE Chair of Renewable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia
Journal Name
Energies
Volume
14
Issue
2
Article Number
en14020295
Year
2021
Publication Date
2021-01-07
ISSN
1996-1073
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PII: en14020295, Publication Type: Journal Article
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LAPSE:2023.28978
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https://doi.org/10.3390/en14020295
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