Biodiesel synthesis from Ceiba pentandra oil by microwave irradiation-assisted transesterification: ELM modeling and optimization
Document Type
Article
Publication Date
1-1-2020
Abstract
In this study, microwave irradiation-assisted transesterification was used to produce Ceiba pentandra biodiesel, which accelerates the rate of reaction and temperature within a shorter period. The improvement of biodiesel production requires a reliable model that accurately reflects the effects of input variables on output variables. In this study, an extreme learning machine integrated with cuckoo search algorithm was developed to predict and optimize the process parameters. This model will be useful for virtual experimentations in order to enhance biodiesel research and development. The optimum parameters of the microwave irradiation-assisted transesterification process conditions were obtained as follows: (1) methanol/oil ratio: 60%, (2) potassium hydroxide catalyst concentration: 0.84%(w/w), (3) stirring speed: 800 rpm, and (4) reaction time: 388 s. The corresponding Ceiba pentandra biodiesel yield was 96.19%. Three independent experiments were conducted using the optimum process parameters and the average biodiesel yield was found to be 95.42%. In conclusion, microwave irradiation-assisted transesterification is an effective method for biodiesel production because it is more energy-efficient, which will reduce the overall cost of biodiesel production. © 2019 Elsevier Ltd
Keywords
Ceiba pentandra biodiesel, Extreme learning machine, Cuckoo search algorithm, Microwave irradiation-assisted transesterification, Alternative fuel
Divisions
fac_eng
Funders
Direktorat Jenderal Penguatan Riset dan Pengembangan Kementerian Riset, Teknologi dan Pendidikan Tinggi Republik Indonesia, (Grant no. 147/SP2H/LT/DRPM/2019),Politeknik Negeri Medan, Medan, Indonesia,AAIBE Chair of Renewable Energy (Grant no: 201801 KETTHA),Universiti Tenaga Nasional Internal Grant (UNIIG 2017) (Grant no.: J510050691),Ministry of Education Malaysia and University of Malaya, Kuala Lumpur Malaysia: FRGS-MRSA ( MO014-2016 )
Publication Title
Renewable Energy
Volume
146
Publisher
Elsevier