RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid
This study is on the modeling of methyl esters production process; obtained by the transesterification of Anacardium occidentale kernel (AOK) oil (AOKO), using artificial neural network (ANN) and response surface methodology (RSM). AOKO was obtained from the kernels/seeds of Anacardium occidentale t...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Current Research in Green and Sustainable Chemistry |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666086521002022 |
| _version_ | 1811196886723330048 |
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| author | Chinedu Matthew Agu Charles Chukwudozie Orakwue Matthew Chukwudi Menkiti Albert Chibuzor Agulanna Florence Chidinma Akaeme |
| author_facet | Chinedu Matthew Agu Charles Chukwudozie Orakwue Matthew Chukwudi Menkiti Albert Chibuzor Agulanna Florence Chidinma Akaeme |
| author_sort | Chinedu Matthew Agu |
| collection | DOAJ |
| description | This study is on the modeling of methyl esters production process; obtained by the transesterification of Anacardium occidentale kernel (AOK) oil (AOKO), using artificial neural network (ANN) and response surface methodology (RSM). AOKO was obtained from the kernels/seeds of Anacardium occidentale tree. The oils were extracted from the kernels using solvent extraction method. The physicochemical properties of AOKO and Anacardium occidentale kernel oil methyl esters (MAOKOt) were determined using standard methods. Fatty acids composition was determined using gas chromatography (GC). At modeling conditions of temperature (65 °C), mole ratio (7:1), catalyst concentration (2.5 wt %), stirring speed (600 rpm) and time (150 min), the RSM predicted and validated methyl ester yields were 94.82%, and 94.70%, respectively; while ANN predicted and validated yields were 93.21% and 93.33%, respectively. The physicochemical characterization results of AOKO and MAOKOt samples, show that their respective viscosity, dielectric strength (DS), pour and flash points were (20.01 and 10.97 mm2s-1), (25.34 and 38.60 kV), (11 and 5 °C), and (270 and 288 °C). These results indicated the MAOKOt sample’s potential use as transformer fluid. The GC result indicated that MAOKOt was unsaturated. Finally, on the basis of the gotten model results, ANN was adjudged as a better predictive model, when compared to RSM. |
| first_indexed | 2024-04-12T01:06:17Z |
| format | Article |
| id | doaj.art-2ed7727328324eff94a990fcc3dc6987 |
| institution | Directory Open Access Journal |
| issn | 2666-0865 |
| language | English |
| last_indexed | 2024-04-12T01:06:17Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Current Research in Green and Sustainable Chemistry |
| spelling | doaj.art-2ed7727328324eff94a990fcc3dc69872022-12-22T03:54:14ZengElsevierCurrent Research in Green and Sustainable Chemistry2666-08652022-01-015100255RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluidChinedu Matthew Agu0Charles Chukwudozie Orakwue1Matthew Chukwudi Menkiti2Albert Chibuzor Agulanna3Florence Chidinma Akaeme4Chemical Engineering Department, Michael Okpara University of Agriculture, Umudike, Nigeria; Corresponding author.Chemical Engineering Department, Nnamdi Azikiwe University, Awka, NigeriaChemical Engineering Department, Nnamdi Azikiwe University, Awka, NigeriaMaterials and Energy Technology Department, Projects Development Institute (PRODA), Emene Industrial Area, Enugu, NigeriaChemical Engineering Department, Nnamdi Azikiwe University, Awka, NigeriaThis study is on the modeling of methyl esters production process; obtained by the transesterification of Anacardium occidentale kernel (AOK) oil (AOKO), using artificial neural network (ANN) and response surface methodology (RSM). AOKO was obtained from the kernels/seeds of Anacardium occidentale tree. The oils were extracted from the kernels using solvent extraction method. The physicochemical properties of AOKO and Anacardium occidentale kernel oil methyl esters (MAOKOt) were determined using standard methods. Fatty acids composition was determined using gas chromatography (GC). At modeling conditions of temperature (65 °C), mole ratio (7:1), catalyst concentration (2.5 wt %), stirring speed (600 rpm) and time (150 min), the RSM predicted and validated methyl ester yields were 94.82%, and 94.70%, respectively; while ANN predicted and validated yields were 93.21% and 93.33%, respectively. The physicochemical characterization results of AOKO and MAOKOt samples, show that their respective viscosity, dielectric strength (DS), pour and flash points were (20.01 and 10.97 mm2s-1), (25.34 and 38.60 kV), (11 and 5 °C), and (270 and 288 °C). These results indicated the MAOKOt sample’s potential use as transformer fluid. The GC result indicated that MAOKOt was unsaturated. Finally, on the basis of the gotten model results, ANN was adjudged as a better predictive model, when compared to RSM.http://www.sciencedirect.com/science/article/pii/S2666086521002022ModelingResponse surface methodologyAnacardium occidentale kernelArtificial neural networkMethyl estersGas chromatography (GC) |
| spellingShingle | Chinedu Matthew Agu Charles Chukwudozie Orakwue Matthew Chukwudi Menkiti Albert Chibuzor Agulanna Florence Chidinma Akaeme RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid Current Research in Green and Sustainable Chemistry Modeling Response surface methodology Anacardium occidentale kernel Artificial neural network Methyl esters Gas chromatography (GC) |
| title | RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid |
| title_full | RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid |
| title_fullStr | RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid |
| title_full_unstemmed | RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid |
| title_short | RSM/ANN based modeling of methyl esters yield from Anacardium occidentale kernel oil by transesterification, for possible application as transformer fluid |
| title_sort | rsm ann based modeling of methyl esters yield from anacardium occidentale kernel oil by transesterification for possible application as transformer fluid |
| topic | Modeling Response surface methodology Anacardium occidentale kernel Artificial neural network Methyl esters Gas chromatography (GC) |
| url | http://www.sciencedirect.com/science/article/pii/S2666086521002022 |
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