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Prediction of performance and exhaust emissions of a CI engine fueled with multi-wall carbon nanotube doped biodiesel-diesel blends using response surface method

This study was designed to analyses the performance and exhaust emissions of a direct-injection diesel engine fueled with multi-walled carbon nanotubes (MWCNTs) included in biodiesel-blended diesel fuel using response surface method (RSM). The influence of input parameters —engine load and MWCNTs co...

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Published in:Energy (Oxford) 2021-07, Vol.227, p.120518, Article 120518
Main Authors: Solmaz, Hamit, Ardebili, Seyed Mohammad Safieddin, Calam, Alper, Yılmaz, Emre, İpci, Duygu
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cited_by cdi_FETCH-LOGICAL-c334t-d9a1b65b78b9fe811fdf3f2b961672c020b356e9b519715729a1d7bab42480ee3
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container_start_page 120518
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creator Solmaz, Hamit
Ardebili, Seyed Mohammad Safieddin
Calam, Alper
Yılmaz, Emre
İpci, Duygu
description This study was designed to analyses the performance and exhaust emissions of a direct-injection diesel engine fueled with multi-walled carbon nanotubes (MWCNTs) included in biodiesel-blended diesel fuel using response surface method (RSM). The influence of input parameters —engine load and MWCNTs concentration — on the response parameters (i.e., BSFC, BTE, CO, NOX, and UHC) were investigated and predicted. MWCNTs were added into B20 fuel (20% biodisesel+80% diesel) in various concentrations (25, 50, 75, and 100 ppm). The tests performed under varying engine load conditions (5, 10, 15, and 20 Nm) at a constant engine speed of 1800 rpm. Multi-regression models for BTE, BSFC, and CO, UHC, and NOX emissions were derived using RSM and were found to be statistically significant. Exhaust UHC and CO concentrations for the studied fuel blend decreases with the addition of MWCNTs into B20 fuel, while NOx emissions drastically increased. The optimal engine working conditions were found to be an engine load of 10 Nm and MWCNTs concentration of 98 ppm. Based on the optimized values, the most optimal results for BTE and BSFC along with CO, UHC, and NOX emissions were found to be 28.57 (%), 269.84 (g/kWh), 0.03 (%Vol.), 44.16 (ppm), and 458.81 (ppm). •Multi-wall carbon nanotube as a fuel additive was added into diesel/biodiesel blend.•Response surface method was employed for engine performance and emission evaluation.•Nano-additives improved engine performance and reduced CO and HC emissions.•High desirability value achieved at an engine load of 10Nm and a dosage of 98 ppm.
doi_str_mv 10.1016/j.energy.2021.120518
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The influence of input parameters —engine load and MWCNTs concentration — on the response parameters (i.e., BSFC, BTE, CO, NOX, and UHC) were investigated and predicted. MWCNTs were added into B20 fuel (20% biodisesel+80% diesel) in various concentrations (25, 50, 75, and 100 ppm). The tests performed under varying engine load conditions (5, 10, 15, and 20 Nm) at a constant engine speed of 1800 rpm. Multi-regression models for BTE, BSFC, and CO, UHC, and NOX emissions were derived using RSM and were found to be statistically significant. Exhaust UHC and CO concentrations for the studied fuel blend decreases with the addition of MWCNTs into B20 fuel, while NOx emissions drastically increased. The optimal engine working conditions were found to be an engine load of 10 Nm and MWCNTs concentration of 98 ppm. Based on the optimized values, the most optimal results for BTE and BSFC along with CO, UHC, and NOX emissions were found to be 28.57 (%), 269.84 (g/kWh), 0.03 (%Vol.), 44.16 (ppm), and 458.81 (ppm). •Multi-wall carbon nanotube as a fuel additive was added into diesel/biodiesel blend.•Response surface method was employed for engine performance and emission evaluation.•Nano-additives improved engine performance and reduced CO and HC emissions.•High desirability value achieved at an engine load of 10Nm and a dosage of 98 ppm.</description><identifier>ISSN: 0360-5442</identifier><identifier>EISSN: 1873-6785</identifier><identifier>DOI: 10.1016/j.energy.2021.120518</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Biodiesel ; Biodiesel fuels ; Biofuels ; Carbon monoxide ; Combustion ; Diesel ; Diesel engines ; Diesel fuels ; Emissions ; Exhaust emissions ; Multi wall carbon nanotubes ; Multi-wall carbon nano tubes ; Nanotechnology ; Nanotubes ; Parameters ; Regression analysis ; Regression models ; Response surface method ; Response surface methodology ; Statistical analysis ; Working conditions</subject><ispartof>Energy (Oxford), 2021-07, Vol.227, p.120518, Article 120518</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright Elsevier BV Jul 15, 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c334t-d9a1b65b78b9fe811fdf3f2b961672c020b356e9b519715729a1d7bab42480ee3</citedby><cites>FETCH-LOGICAL-c334t-d9a1b65b78b9fe811fdf3f2b961672c020b356e9b519715729a1d7bab42480ee3</cites><orcidid>0000-0003-0689-6824</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids></links><search><creatorcontrib>Solmaz, Hamit</creatorcontrib><creatorcontrib>Ardebili, Seyed Mohammad Safieddin</creatorcontrib><creatorcontrib>Calam, Alper</creatorcontrib><creatorcontrib>Yılmaz, Emre</creatorcontrib><creatorcontrib>İpci, Duygu</creatorcontrib><title>Prediction of performance and exhaust emissions of a CI engine fueled with multi-wall carbon nanotube doped biodiesel-diesel blends using response surface method</title><title>Energy (Oxford)</title><description>This study was designed to analyses the performance and exhaust emissions of a direct-injection diesel engine fueled with multi-walled carbon nanotubes (MWCNTs) included in biodiesel-blended diesel fuel using response surface method (RSM). 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1873-6785
language eng
recordid cdi_proquest_journals_2540549680
source Elsevier
subjects Biodiesel
Biodiesel fuels
Biofuels
Carbon monoxide
Combustion
Diesel
Diesel engines
Diesel fuels
Emissions
Exhaust emissions
Multi wall carbon nanotubes
Multi-wall carbon nano tubes
Nanotechnology
Nanotubes
Parameters
Regression analysis
Regression models
Response surface method
Response surface methodology
Statistical analysis
Working conditions
title Prediction of performance and exhaust emissions of a CI engine fueled with multi-wall carbon nanotube doped biodiesel-diesel blends using response surface method
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