Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine

accuracy assessment; biofuel; combustion; diesel engine; exhaust emission; industrial emission; machine learning; numerical model; parameter estimation; performance assessment; software; testing method; Jatropha curcas; biofuel; gasoline; analysis; chemistry; exhaust gas; Jatropha; machine learning;...

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Main Authors: Silitonga A.S., Hassan M.H., Ong H.C., Kusumo F.
Other Authors: 39262559400
Format: Article
Published: Springer Verlag 2023
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spelling my.uniten.dspace-230682023-05-29T14:37:39Z Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine Silitonga A.S. Hassan M.H. Ong H.C. Kusumo F. 39262559400 9232771700 55310784800 56611974900 accuracy assessment; biofuel; combustion; diesel engine; exhaust emission; industrial emission; machine learning; numerical model; parameter estimation; performance assessment; software; testing method; Jatropha curcas; biofuel; gasoline; analysis; chemistry; exhaust gas; Jatropha; machine learning; Biofuels; Gasoline; Jatropha; Machine Learning; Vehicle Emissions The purpose of this study is to investigate the performance, emission and combustion characteristics of a four-cylinder common-rail turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends. A kernel-based extreme learning machine (KELM) model is developed in this study using MATLAB software in order to predict the performance, combustion and emission characteristics of the engine. To acquire the data for training and testing the KELM model, the engine speed was selected as the input parameter, whereas the performance, exhaust emissions and combustion characteristics were chosen as the output parameters of the KELM model. The performance, emissions and combustion characteristics predicted by the KELM model were validated by comparing the predicted data with the experimental data. The results show that the coefficient of determination of the parameters is within a range of 0.9805�0.9991 for both the KELM model and the experimental data. The mean absolute percentage error is within a range of 0.1259�2.3838. This study shows that KELM modelling is a useful technique in biodiesel production since it facilitates scientists and researchers to predict the performance, exhaust emissions and combustion characteristics of internal combustion engines with high accuracy. � 2017, Springer-Verlag GmbH Germany. Final 2023-05-29T06:37:39Z 2023-05-29T06:37:39Z 2017 Article 10.1007/s11356-017-0141-9 2-s2.0-85029602552 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029602552&doi=10.1007%2fs11356-017-0141-9&partnerID=40&md5=73b05161c692246082c02fe2bd72606e https://irepository.uniten.edu.my/handle/123456789/23068 24 32 25383 25405 Springer Verlag Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description accuracy assessment; biofuel; combustion; diesel engine; exhaust emission; industrial emission; machine learning; numerical model; parameter estimation; performance assessment; software; testing method; Jatropha curcas; biofuel; gasoline; analysis; chemistry; exhaust gas; Jatropha; machine learning; Biofuels; Gasoline; Jatropha; Machine Learning; Vehicle Emissions
author2 39262559400
author_facet 39262559400
Silitonga A.S.
Hassan M.H.
Ong H.C.
Kusumo F.
format Article
author Silitonga A.S.
Hassan M.H.
Ong H.C.
Kusumo F.
spellingShingle Silitonga A.S.
Hassan M.H.
Ong H.C.
Kusumo F.
Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
author_sort Silitonga A.S.
title Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
title_short Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
title_full Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
title_fullStr Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
title_full_unstemmed Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
title_sort analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine
publisher Springer Verlag
publishDate 2023
_version_ 1806426709294055424
score 13.222552