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
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
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 H-2 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 H-2 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 H-2 feeding rate while 5.5 g/h H-2 addition with modified ternary blend fuel would be the optimal.
Açıklama
Anahtar Kelimeler
Nano additive, TiO (2) and MWCNT, Hydrogen, N-Butanol, Optimization with ANN model
Kaynak
Fuel Processing Technology
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
229
