Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN)
In this study, an unexplored oil from the wodyetia bifurcata fruit was used for biodiesel production. The transesterification process was implemented to convert the raw oil into wodyetia bifurcata methyl ester (WBME) and the influence of process variables on WBME yield was examined with the response...
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| Format: | Article |
| Language: | English |
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Universitas Muhammadiyah Magelang
2021-11-01
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| Series: | Automotive Experiences |
| Subjects: | |
| Online Access: | https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/6171 |
| _version_ | 1818904214989963264 |
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| author | Aditya Kolakoti Bobbili Prasadarao Katakam Satyanarayana Muji Setiyo Hasan Köten Metta Raghu |
| author_facet | Aditya Kolakoti Bobbili Prasadarao Katakam Satyanarayana Muji Setiyo Hasan Köten Metta Raghu |
| author_sort | Aditya Kolakoti |
| collection | DOAJ |
| description | In this study, an unexplored oil from the wodyetia bifurcata fruit was used for biodiesel production. The transesterification process was implemented to convert the raw oil into wodyetia bifurcata methyl ester (WBME) and the influence of process variables on WBME yield was examined with the response surface method (RSM) assisted Box-Behnken optimization. The results of RSM show that a maximum biodiesel yield of 94.67% was achieved and reaction time was identified as an influencing process variable. The fatty acid composition (FAC) from chromatography reveals the presence of highly unsaturated in WBME and the significant fuel properties of thermal and molecular meet the required fuel standards (ASTM). The obtained fuel properties of WBME are compared with other popularly used biodiesels and observed low kinematic viscosity (3.87mm2/sec) and moderated cetane number (53) for WBME. Furthermore, artificial neural network (ANN) tools are used for the prediction of WBME yield and show an improvement of 0.4% than RSM and low mean square error and a high coefficient of correlation was observed for ANN. |
| first_indexed | 2024-12-19T21:03:53Z |
| format | Article |
| id | doaj.art-463383736aa94b02952dc95654560ed7 |
| institution | Directory Open Access Journal |
| issn | 2615-6202 2615-6636 |
| language | English |
| last_indexed | 2024-12-19T21:03:53Z |
| publishDate | 2021-11-01 |
| publisher | Universitas Muhammadiyah Magelang |
| record_format | Article |
| series | Automotive Experiences |
| spelling | doaj.art-463383736aa94b02952dc95654560ed72022-12-21T20:05:43ZengUniversitas Muhammadiyah MagelangAutomotive Experiences2615-62022615-66362021-11-015110.31603/ae.6171Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN)Aditya Kolakoti0Bobbili Prasadarao1Katakam Satyanarayana2Muji Setiyo3Hasan Köten4Metta Raghu5Raghu Engineering College, IndiaVignan’s Institute of Information Technology, IndiaANITS Engineering College, IndiaUniversitas Muhammadiyah Magelang, IndonesiaIstanbul Medeniyet University, TurkeyRaghu Engineering College, IndiaIn this study, an unexplored oil from the wodyetia bifurcata fruit was used for biodiesel production. The transesterification process was implemented to convert the raw oil into wodyetia bifurcata methyl ester (WBME) and the influence of process variables on WBME yield was examined with the response surface method (RSM) assisted Box-Behnken optimization. The results of RSM show that a maximum biodiesel yield of 94.67% was achieved and reaction time was identified as an influencing process variable. The fatty acid composition (FAC) from chromatography reveals the presence of highly unsaturated in WBME and the significant fuel properties of thermal and molecular meet the required fuel standards (ASTM). The obtained fuel properties of WBME are compared with other popularly used biodiesels and observed low kinematic viscosity (3.87mm2/sec) and moderated cetane number (53) for WBME. Furthermore, artificial neural network (ANN) tools are used for the prediction of WBME yield and show an improvement of 0.4% than RSM and low mean square error and a high coefficient of correlation was observed for ANN.https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/6171Wodyetia BifurcataBiodieselFoxtail treeFuel propertiesANNRSM |
| spellingShingle | Aditya Kolakoti Bobbili Prasadarao Katakam Satyanarayana Muji Setiyo Hasan Köten Metta Raghu Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN) Automotive Experiences Wodyetia Bifurcata Biodiesel Foxtail tree Fuel properties ANN RSM |
| title | Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN) |
| title_full | Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN) |
| title_fullStr | Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN) |
| title_full_unstemmed | Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN) |
| title_short | Elemental, Thermal and Physicochemical Investigation of Novel Biodiesel from Wodyetia Bifurcata and Its Properties Optimization using Artificial Neural Network (ANN) |
| title_sort | elemental thermal and physicochemical investigation of novel biodiesel from wodyetia bifurcata and its properties optimization using artificial neural network ann |
| topic | Wodyetia Bifurcata Biodiesel Foxtail tree Fuel properties ANN RSM |
| url | https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/6171 |
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