Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and tes...

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Main Authors:	Ghanbari, M., Najafi, G., Ghobadian, B., R., Mamat, M. M., Noor, A., Moosavian
Format:	Conference or Workshop Item
Language:	English
Published:	IOP Publishing Ltd 2015
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/24749/ http://umpir.ump.edu.my/id/eprint/24749/ http://umpir.ump.edu.my/id/eprint/24749/1/Support%20Vector%20Machine%20to%20predict%20diesel%20engine%20performance%20and%20emission%20parameters%20fueled%20with%20nano-particles%20additive%20to%20diesel%20fuel.pdf

id	ump-24749
recordtype	eprints
spelling	ump-247492019-07-04T04:02:50Z http://umpir.ump.edu.my/id/eprint/24749/ Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel Ghanbari, M. Najafi, G. Ghobadian, B. R., Mamat M. M., Noor A., Moosavian TJ Mechanical engineering and machinery This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly. IOP Publishing Ltd 2015 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24749/1/Support%20Vector%20Machine%20to%20predict%20diesel%20engine%20performance%20and%20emission%20parameters%20fueled%20with%20nano-particles%20additive%20to%20diesel%20fuel.pdf Ghanbari, M. and Najafi, G. and Ghobadian, B. and R., Mamat and M. M., Noor and A., Moosavian (2015) Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel. In: 3rd International Conference of Mechanical Engineering Research (ICMER 2015), 18-19 August 2015 , Kuantan, Pahang. pp. 1-8., 100 (012069). ISSN 17578981 https://iopscience.iop.org/article/10.1088/1757-899X/100/1/012069/meta
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Ghanbari, M. Najafi, G. Ghobadian, B. R., Mamat M. M., Noor A., Moosavian Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
description	This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.
format	Conference or Workshop Item
author	Ghanbari, M. Najafi, G. Ghobadian, B. R., Mamat M. M., Noor A., Moosavian
author_facet	Ghanbari, M. Najafi, G. Ghobadian, B. R., Mamat M. M., Noor A., Moosavian
author_sort	Ghanbari, M.
title	Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
title_short	Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
title_full	Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
title_fullStr	Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
title_full_unstemmed	Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
title_sort	support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel
publisher	IOP Publishing Ltd
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/24749/ http://umpir.ump.edu.my/id/eprint/24749/ http://umpir.ump.edu.my/id/eprint/24749/1/Support%20Vector%20Machine%20to%20predict%20diesel%20engine%20performance%20and%20emission%20parameters%20fueled%20with%20nano-particles%20additive%20to%20diesel%20fuel.pdf
first_indexed	2023-09-18T22:37:38Z
last_indexed	2023-09-18T22:37:38Z
_version_	1777416702583111680

Support Vector Machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

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