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Dual effects of N-butanol and magnetite nanoparticle to biodiesel-diesel fuel blends as additives on emission pattern and performance of a diesel engine with ANN validation

Sule, Ahmed and Abdul Latiff, Zulkarnain and Abas, Mohd. Azman and Veza, Ibham and Soudagar, Manzoore Elahi M. and Irianto Harny, Irianto Harny and Epin, Vorathin (2023) Dual effects of N-butanol and magnetite nanoparticle to biodiesel-diesel fuel blends as additives on emission pattern and performance of a diesel engine with ANN validation. Sustainability (Switzerland), 15 (2). pp. 1-22. ISSN 2071-1050

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Official URL: http://dx.doi.org/10.3390/su15021404

Abstract

This paper investigates impact of magnetite dispersed in butanol and added to two varied blends of palm biodiesel and diesel (B20 and B30). The developed fuel samples were characterized and tested on single cylinder diesel Yanmar engine (L70N) to observe engine behavior for emissions and performance. Results are compared with two reference fuels: YF50 fuel contains 50 ppm magnetite in B20 and Bn10Y90 contains 10% butanol with 90% B20. Addition of magnetite and butanol depletes emissions levels and improve performance compared to ordinary B20 and B30 however; samples with higher dosage of magnetite (150 ppm) yielded better results in performance and emission compared with lower dosage (75 ppm). The best sample was C10Z90 which entails 150 ppm magnetite in butanol added at 10% to B30. Brake thermal efficiency (BTE) at highest brake power (BP) point for C10Z90 was 37.28% compared to others (32.88%, 35.22% and 35.96%). Additionally, brake specific fuel consumption (BSFC) of C10Z90 was at least 8.29 g/Kw.hr and at most 84.52 g/Kw.hr less than other samples at highest BP point. Results indicated C10Z90 was lower in carbon-monoxide, hydrocarbon and smoke except for oxides of nitrogen. Artificial Neural Network (ANN) model successfully predicted BTE, BSFC and emissions of the dual fuel application.

Item Type:Article
Uncontrolled Keywords:ANN model, butanol, efficiency, emissions
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:107257
Deposited By: Yanti Mohd Shah
Deposited On:01 Sep 2024 06:29
Last Modified:01 Sep 2024 06:29

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