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akaturk Akademik ölçüm

Makale detayı · 2025 · article

Application of RSM for prediction and optimization of performance and emissions of diesel engine fuelled with butanol-diesel blends

Dergi International Journal of Automotive Engineering and Technologies
ISSN2146 - 9067
YÖKSİS OpenAlex Açık erişim · diamond
Yıl2025
Atıf1OpenAlex
Yüzdelik%47,1
FWCI0,341,00 = dünya ortalaması

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıInternational Journal of Automotive Engineering and Technologies
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

This work investigated the impacts of butanol-diesel fuel blends used in a turbocharged six-cylinder heavy-duty diesel engine on engine performance and exhaust emission parameters. It evaluated their optimization by using response surface methodology. The engine's operational factors, such as engine speed and the proportion of butanol-diesel fuel blend, have been optimized to attain optimal engine performance and exhaust emissions. The model was designed by Central Composite Design using Minitab software (trial version) and confirmed by the experimental results. According to RSM, the optimum blend ratio of butanol-diesel fuel and engine speed were 5% and 1721.4 rpm, respectively. Optimum desirability is found as 0.6260 with a butanol- diesel fuel blend of 5% and 1721.4 rpm engine speed for the heavy-duty diesel engine. The responses obtained under optimal conditions were determined as 821.19 Nm for torque, 158.1 kW for power, 895.7 ppm for NOx, 104.05 ppm for CO, and 21.14 ppm for HC, respectively. The values for the R2 coefficient determination were 99.02%, 99.98%, 99.67%, 99.97%, and 99.95%, respectively.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

1atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yerel katalogda bu makaleye atıf yapan 4 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).

  1. 2026 Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel EnginesAtıf 0 · OpenAlex
  2. 2026 Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel EnginesAtıf 0 · OpenAlex
  3. 2026 Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel EnginesAtıf 0 · OpenAlex
  4. 2026 Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel EnginesAtıf 0 · OpenAlex

Yazarlar

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  1. CEYLA GÜNGÖR ADANA ALPARSLAN TÜRKEŞ BİLİM VE TEKNOLOJİ ÜNİVERSİTESİ 1