Experimental study and prediction of the performance and exhaust emissions of mixed Jatropha curcas-Ceiba pentandra biodiesel blends in diesel engine using artificial neural networks

Dharma, S; Hassan, MH; Ong, HC; Sebayang, AH; Silitonga, AS; Kusumo, F; Milano, J

Experimental study and prediction of the performance and exhaust emissions of mixed Jatropha curcas-Ceiba pentandra biodiesel blends in diesel engine using artificial neural networks

Dharma, S Hassan, MH Ong, HC Sebayang, AH Silitonga, AS Kusumo, F Milano, J

Permalink

Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Journal of Cleaner Production, 2017, 164, pp. 618-633
Issue Date:: 2017-10-15

Closed Access

	Filename	Description	Size
	1-s2.0-S0959652617312350-main.pdf		1.65 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Dharma, S
dc.contributor.author	Hassan, MH
dc.contributor.author	Ong, HC
dc.contributor.author	Sebayang, AH
dc.contributor.author	Silitonga, AS
dc.contributor.author	Kusumo, F
dc.contributor.author	Milano, J
dc.date.accessioned	2022-09-07T05:34:47Z
dc.date.available	2022-09-07T05:34:47Z
dc.date.issued	2017-10-15
dc.identifier.citation	Journal of Cleaner Production, 2017, 164, pp. 618-633
dc.identifier.issn	0959-6526
dc.identifier.issn	1879-1786
dc.identifier.uri	http://hdl.handle.net/10453/161463
dc.description.abstract	The depletion of oil reserves as well as environmental pollution resulting from the burning of fossil fuels has led to ongoing research and development of biodiesels in order to substitute fossil fuels. The objective of this study is to investigate the performance and exhaust emissions of a single-cylinder direct injection diesel engine fueled with Jatropa curcas-Ceiba pentandra biodiesel-diesel blends. The Jatropa curcas-Ceiba pentandra biodiesel (J50C50) is produced by mixing the crude oils at an equal volume ratio, followed by degumming, acid-catalyzed esterification, and alkaline-catalyzed transesterification. The B10, B20, B30, B40, and B50 blends are produced by blending 10, 20, 30, 40, and 50 vol% of J50C50 biodiesel with diesel. In general, the engine performance of B10 is close to that of diesel fuel, and facilitates achieving higher engine torque, brake power, and brake thermal efficiency comparable to other blends. Blending J50C50 biodiesel with diesel reduces the carbon dioxide emissions and smoke opacity, but increases the nitrogen oxide and carbon monoxide emissions. In addition, artificial neural network models are developed to predict the engine performance and exhaust emission parameters, and the models give excellent results, whereby the coefficient of determination is more than 98% and the mean absolute percentage error is less than 5% for all parameters. In general, the artificial neural network models give accurate and reliable results, without the need for an explicit mathematical representation. Based on the results, it can be concluded that the J50C50 biodiesel-diesel blends qualify as alternative fuels in diesel engines.
dc.language	English
dc.publisher	Elsevier
dc.relation.ispartof	Journal of Cleaner Production
dc.relation.isbasedon	10.1016/j.jclepro.2017.06.065
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0907 Environmental Engineering, 0910 Manufacturing Engineering, 0915 Interdisciplinary Engineering
dc.subject.classification	Environmental Sciences
dc.title	Experimental study and prediction of the performance and exhaust emissions of mixed Jatropha curcas-Ceiba pentandra biodiesel blends in diesel engine using artificial neural networks
dc.type	Journal Article
utslib.citation.volume	164
utslib.for	0907 Environmental Engineering
utslib.for	0910 Manufacturing Engineering
utslib.for	0915 Interdisciplinary Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-09-07T05:34:45Z
pubs.publication-status	Published
pubs.volume	164

Abstract:

The depletion of oil reserves as well as environmental pollution resulting from the burning of fossil fuels has led to ongoing research and development of biodiesels in order to substitute fossil fuels. The objective of this study is to investigate the performance and exhaust emissions of a single-cylinder direct injection diesel engine fueled with Jatropa curcas-Ceiba pentandra biodiesel-diesel blends. The Jatropa curcas-Ceiba pentandra biodiesel (J50C50) is produced by mixing the crude oils at an equal volume ratio, followed by degumming, acid-catalyzed esterification, and alkaline-catalyzed transesterification. The B10, B20, B30, B40, and B50 blends are produced by blending 10, 20, 30, 40, and 50 vol% of J50C50 biodiesel with diesel. In general, the engine performance of B10 is close to that of diesel fuel, and facilitates achieving higher engine torque, brake power, and brake thermal efficiency comparable to other blends. Blending J50C50 biodiesel with diesel reduces the carbon dioxide emissions and smoke opacity, but increases the nitrogen oxide and carbon monoxide emissions. In addition, artificial neural network models are developed to predict the engine performance and exhaust emission parameters, and the models give excellent results, whereby the coefficient of determination is more than 98% and the mean absolute percentage error is less than 5% for all parameters. In general, the artificial neural network models give accurate and reliable results, without the need for an explicit mathematical representation. Based on the results, it can be concluded that the J50C50 biodiesel-diesel blends qualify as alternative fuels in diesel engines.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/161463