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Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology

[Image: see text] The ongoing depletion of the world’s fossil fuel sources and environmental damage has compelled the quest for alternative energy. Excellent characteristics of biodiesel include its renewable nature, safety, absence of sulfur, environmental advantages, and biodegradability, which ca...

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Autores principales: Ramachandran, Elumalai, Krishnaiah, Ravi, Venkatesan, Elumalai Perumal, Murugan, Manickam, Medapati, Sreenivasa Reddy, Sekar, Prabhakar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018500/
https://www.ncbi.nlm.nih.gov/pubmed/36936311
http://dx.doi.org/10.1021/acsomega.2c07104
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author Ramachandran, Elumalai
Krishnaiah, Ravi
Venkatesan, Elumalai Perumal
Murugan, Manickam
Medapati, Sreenivasa Reddy
Sekar, Prabhakar
author_facet Ramachandran, Elumalai
Krishnaiah, Ravi
Venkatesan, Elumalai Perumal
Murugan, Manickam
Medapati, Sreenivasa Reddy
Sekar, Prabhakar
author_sort Ramachandran, Elumalai
collection PubMed
description [Image: see text] The ongoing depletion of the world’s fossil fuel sources and environmental damage has compelled the quest for alternative energy. Excellent characteristics of biodiesel include its renewable nature, safety, absence of sulfur, environmental advantages, and biodegradability, which can eradicate the above problems. In this study, algal oil was characterized to obtain the fatty acid profile, and the free fatty acid value of algal oil suggested a two-step process of esterification and transesterification for efficient biodiesel production. The performance and emission results of biodiesel and its blends (B10, B20, and B30) were investigated in a constant speed, single-cylinder, 4-stroke, 3.5 kW compression ignition engine at different loads for arriving at an appropriate fuel blend ratio. The response surface methodology technique is used to predict the ideal composition of microalgae–diesel using the experimental data with due weightage for the optimization criterion. The predicted blend ratio of B25 was tested on the engine and authenticated. The findings recorded an improvement in brake thermal efficiency to 31.42% and reduction in brake specific energy consumption to 9.82 MJ/kW h, unburned hydrocarbon to 85 ppm, carbon monoxide to 0.164% v/v, carbon dioxide to 4.115% v/v, nitrogen oxides to 691 ppm, and smoke opacity to 16.93%.
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spelling pubmed-100185002023-03-17 Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology Ramachandran, Elumalai Krishnaiah, Ravi Venkatesan, Elumalai Perumal Murugan, Manickam Medapati, Sreenivasa Reddy Sekar, Prabhakar ACS Omega [Image: see text] The ongoing depletion of the world’s fossil fuel sources and environmental damage has compelled the quest for alternative energy. Excellent characteristics of biodiesel include its renewable nature, safety, absence of sulfur, environmental advantages, and biodegradability, which can eradicate the above problems. In this study, algal oil was characterized to obtain the fatty acid profile, and the free fatty acid value of algal oil suggested a two-step process of esterification and transesterification for efficient biodiesel production. The performance and emission results of biodiesel and its blends (B10, B20, and B30) were investigated in a constant speed, single-cylinder, 4-stroke, 3.5 kW compression ignition engine at different loads for arriving at an appropriate fuel blend ratio. The response surface methodology technique is used to predict the ideal composition of microalgae–diesel using the experimental data with due weightage for the optimization criterion. The predicted blend ratio of B25 was tested on the engine and authenticated. The findings recorded an improvement in brake thermal efficiency to 31.42% and reduction in brake specific energy consumption to 9.82 MJ/kW h, unburned hydrocarbon to 85 ppm, carbon monoxide to 0.164% v/v, carbon dioxide to 4.115% v/v, nitrogen oxides to 691 ppm, and smoke opacity to 16.93%. American Chemical Society 2023-03-06 /pmc/articles/PMC10018500/ /pubmed/36936311 http://dx.doi.org/10.1021/acsomega.2c07104 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Ramachandran, Elumalai
Krishnaiah, Ravi
Venkatesan, Elumalai Perumal
Murugan, Manickam
Medapati, Sreenivasa Reddy
Sekar, Prabhakar
Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology
title Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology
title_full Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology
title_fullStr Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology
title_full_unstemmed Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology
title_short Experimental Investigation for Determining an Ideal Algal Biodiesel–Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology
title_sort experimental investigation for determining an ideal algal biodiesel–diesel blend to improve the performance and mitigate emissions using a response surface methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018500/
https://www.ncbi.nlm.nih.gov/pubmed/36936311
http://dx.doi.org/10.1021/acsomega.2c07104
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