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An Intelligent Artificial Neural Network-Response Surface Methodology Method for Accessing the Optimum Biodiesel and Diesel Fuel Blending Conditions in a Diesel Engine from the Viewpoint of Exergy and Energy Analysis

  • Biodiesel, as the main alternative fuel to diesel fuel which is produced from renewable and available resources, improves the engine emissions during combustion in diesel engines. In this study, the biodiesel is produced initially from waste cooking oil (WCO). The fuel samples are applied in a diesel engine and the engine performance has been considered from the viewpoint of exergy and energyBiodiesel, as the main alternative fuel to diesel fuel which is produced from renewable and available resources, improves the engine emissions during combustion in diesel engines. In this study, the biodiesel is produced initially from waste cooking oil (WCO). The fuel samples are applied in a diesel engine and the engine performance has been considered from the viewpoint of exergy and energy approaches. Engine tests are performed at a constant 1500 rpm speed with various loads and fuel samples. The obtained experimental data are also applied to develop an artificial neural network (ANN) model. Response surface methodology (RSM) is employed to optimize the exergy and energy efficiencies. Based on the results of the energy analysis, optimal engine performance is obtained at 80% of full load in presence of B10 and B20 fuels. However, based on the exergy analysis results, optimal engine performance is obtained at 80% of full load in presence of B90 and B100 fuels. The optimum values of exergy and energy efficiencies are in the range of 25–30% of full load, which is the same as the calculated range obtained from mathematical modeling.show moreshow less

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    Gefördert aus Mitteln des Open-Access-Publikationsfonds' der Bauhaus-Universität Weimar und vom Thüringer Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft (TMWWDG).

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Document Type:Article
Author:Dr. Amir MosaviORCiD, Bahman NajafiORCiDGND, Sina Faizollahzadeh ArdabiliORCiD, Shahaboddin ShamshirbandORCiD, Timon RabczukORCiDGND
DOI (Cite-Link):https://doi.org/10.3390/en11040860Cite-Link
URN (Cite-Link):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20180507-37467Cite-Link
URL:http://www.mdpi.com/1996-1073/11/4/860
Parent Title (English):Energies
Publisher:MDPI
Place of publication:Basel
Language:English
Date of Publication (online):2018/04/07
Date of first Publication:2018/04/07
Release Date:2018/05/07
Publishing Institution:Bauhaus-Universität Weimar
Institutes:Fakultät Bauingenieurwesen / Institut für Strukturmechanik
Volume:2018
Issue:11, 4
Pagenumber:18
Tag:ANN modeling; Artificial Intelligence; biodiesel; diesel engines; energy, exergy; mathematical modeling
GND Keyword:Biodiesel
Dewey Decimal Classification:300 Sozialwissenschaften / 330 Wirtschaft / 333 Boden- und Energiewirtschaft
600 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften / 621 Angewandte Physik
BKL-Classification:48 Land- und Forstwirtschaft / 48.30 Natürliche Ressourcen
52 Maschinenbau, Energietechnik, Fertigungstechnik / 52.56 Regenerative Energieformen, alternative Energieformen
Open Access Publikationsfonds:Open-Access-Publikationsfonds 2018
Licence (German):License Logo Creative Commons 4.0 - Namensnennung (CC BY 4.0)