Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods
Flash point is one of the most important propertiesof engine fuel that indicatesthe lowest temperature at which sufficient flammable vapours have evaporatedto allow for ignition. In this paper, the applicability of Liaw Model to predictthe flash point of miscible tailor4made green diesel blends thro...
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my.utm.578032021-12-15T07:13:32Z http://eprints.utm.my/id/eprint/57803/ Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods Phoon, L. Y. Hashim, H. Mat, R. Mustaffa, A. A. TP Chemical technology Flash point is one of the most important propertiesof engine fuel that indicatesthe lowest temperature at which sufficient flammable vapours have evaporatedto allow for ignition. In this paper, the applicability of Liaw Model to predictthe flash point of miscible tailor4made green diesel blends through UNIFACtype models (Original UNIFAC and Modified UNIFAC (Dortmund)) isanalyzed. The predictions are compared with the experimental data of pseudo4binary mixtures of B5 palm oil biodiesel with lignocellulosic biofuel (ethyllevulinate, dibutyl ether, dipentyl ether, 14propanol, 14butanol, 14pentanol and14hexanol). The prediction accuracy is evaluated using the Average AbsoluteRelative Deviation (AARD) between the experimentaldata and the predictedvalues. The predictions for B54ethyl levulinate areclose to the data (AARD =1.2% and 1.5% for UNIFAC and Modified UNIFAC (Dortmund) models,respectively) even though the flash point of the mixture is below the flash pointof individual components. On the other hand, the AARD values obtained usingOriginal UNIFAC are 1.7% and 3.2% for B54dibutyl ether and B54dipentylether while using Modified UNIFAC (Dortmund), the AARD obtained are1.7% and 3.3%, respectively. For the B54alcohol blends, the AARD valuesobtained for B5414propanol, B5414butanol, B5414pentanol and B5414hexanolblends are 32.2%, 8.7%, 4.6% and 3.1% respectivelyfor original UNIFAC and30.6%, 7.4%, 4.1% and 3.3% respectively for Modified UNIFAC (Dortmund).The prediction accuracy of the model is decreasingwith the decrease of thecarbon chain length in the alcohol. Overall, the Liaw Model that is incorporatedwith either Original UNIFAC or Modified UNIFAC (Dortmund) has similarprediction accuracy. Liaw Model using UNIFAC type models generalized theflash point predictions for different green dieselblends. However, theprediction accuracy for B54alcohol blends need to be improve further whichwill be part of the future work. Taylor's University 2015 Article PeerReviewed Phoon, L. Y. and Hashim, H. and Mat, R. and Mustaffa, A. A. (2015) Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods. Journal Of Engineering Science And Technology, 10 . pp. 110-119. ISSN 1819-6608 |
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TP Chemical technology Phoon, L. Y. Hashim, H. Mat, R. Mustaffa, A. A. Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods |
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Flash point is one of the most important propertiesof engine fuel that indicatesthe lowest temperature at which sufficient flammable vapours have evaporatedto allow for ignition. In this paper, the applicability of Liaw Model to predictthe flash point of miscible tailor4made green diesel blends through UNIFACtype models (Original UNIFAC and Modified UNIFAC (Dortmund)) isanalyzed. The predictions are compared with the experimental data of pseudo4binary mixtures of B5 palm oil biodiesel with lignocellulosic biofuel (ethyllevulinate, dibutyl ether, dipentyl ether, 14propanol, 14butanol, 14pentanol and14hexanol). The prediction accuracy is evaluated using the Average AbsoluteRelative Deviation (AARD) between the experimentaldata and the predictedvalues. The predictions for B54ethyl levulinate areclose to the data (AARD =1.2% and 1.5% for UNIFAC and Modified UNIFAC (Dortmund) models,respectively) even though the flash point of the mixture is below the flash pointof individual components. On the other hand, the AARD values obtained usingOriginal UNIFAC are 1.7% and 3.2% for B54dibutyl ether and B54dipentylether while using Modified UNIFAC (Dortmund), the AARD obtained are1.7% and 3.3%, respectively. For the B54alcohol blends, the AARD valuesobtained for B5414propanol, B5414butanol, B5414pentanol and B5414hexanolblends are 32.2%, 8.7%, 4.6% and 3.1% respectivelyfor original UNIFAC and30.6%, 7.4%, 4.1% and 3.3% respectively for Modified UNIFAC (Dortmund).The prediction accuracy of the model is decreasingwith the decrease of thecarbon chain length in the alcohol. Overall, the Liaw Model that is incorporatedwith either Original UNIFAC or Modified UNIFAC (Dortmund) has similarprediction accuracy. Liaw Model using UNIFAC type models generalized theflash point predictions for different green dieselblends. However, theprediction accuracy for B54alcohol blends need to be improve further whichwill be part of the future work. |
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Article |
author |
Phoon, L. Y. Hashim, H. Mat, R. Mustaffa, A. A. |
author_facet |
Phoon, L. Y. Hashim, H. Mat, R. Mustaffa, A. A. |
author_sort |
Phoon, L. Y. |
title |
Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods |
title_short |
Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods |
title_full |
Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods |
title_fullStr |
Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods |
title_full_unstemmed |
Analysis of flash point predictions of tailor-made green diesel by UNIFAC group contribution methods |
title_sort |
analysis of flash point predictions of tailor-made green diesel by unifac group contribution methods |
publisher |
Taylor's University |
publishDate |
2015 |
url |
http://eprints.utm.my/id/eprint/57803/ |
_version_ |
1720436853590458368 |
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13.160551 |