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Investigation of a ternary blend of diesel/ethanol/n-butanol with binary nano additives on combustion and emission: A modeling and optimization approach with artificial neural networks   
Yazarlar (1)
Doç. Dr. Muhammed Raşit ATELGE Doç. Dr. Muhammed Raşit ATELGE
Kastamonu Üniversitesi, Türkiye
Devamını Göster
Özet
The increase in global energy consumption and concerns about fossil fuels depletion are pushing the demand for renewable and clean energy sources. Alcohols are a promising candidate for internal combustion engines as alternative fuels. This study aims to reveal the effect of a ternary blend, which is denominated D80E10nB10, consisting of diesel (80%), ethanol (10%), and n-butanol (10%) on combustion and emission characteristics. The addition of both metal oxide (TiO2) and nonmetallic nanoparticle (MWCNT) was also investigated with the above-mentioned ternary blend fuels, which are denominated “m-”. The compression ignition engine was run under dual fuel mode with feeding H2 in the range of 5 and 15 g/h, which were labeled D80E10nB10H5 and 15. The results revealed that the maximum pressure increased by 3.63 and 3.94% by adding 5 and 15 g/h H2 respectively into ternary blend fuel under the full load. The highest BTE was obtained from modified diesel fuel which was 23.24% higher than diesel. Furthermore, 60 Artificial Neural Network (ANN) models were built to optimize test conditions. The optimal conditions for ternary blend fuel were found to be 4 g/h H2 feeding rate while 5.5 g/h H2 addition with modified ternary blend fuel would be the optimal.
Anahtar Kelimeler
Hydrogen | N-Butanol | Nano additive | Optimization with ANN model | TiO and MWCNT 2
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale
Dergi Adı Fuel Processing Technology
Dergi ISSN 0378-3820
Dergi Tarandığı Indeksler SCI-Expanded
Dergi Grubu Q1
Makale Dili İngilizce
Basım Tarihi 05-2022
Cilt No 229
Sayı 1
Sayfalar 1 / 15
Doi Numarası 10.1016/j.fuproc.2021.107155
Makale Linki http://dx.doi.org/10.1016/j.fuproc.2021.107155