Prediction of performance and exhaust emissions of a CI engine fueled with multi-wall carbon nanotube doped biodiesel-diesel blends using response surface method

Solmaz H., Ardebili S. M. S., Calam A., Yılmaz E., İpci D.

Energy, cilt.227, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 227
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.energy.2021.120518
  • Dergi Adı: Energy
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Computer & Applied Sciences, Environment Index, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Performance, Emissions, Multi-wall carbon nano tubes, Combustion, Biodiesel, Response surface method, COMPRESSION IGNITION, COMBUSTION CHARACTERISTICS, VEGETABLE-OIL, ADDITIVES, IMPROVE, ESTER, OPTIMIZATION, REDUCE, EGR, STRATEGIES
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2021 Elsevier LtdThis study was designed to analyses the performance and exhaust emissions of a direct-injection diesel engine fueled with multi-walled carbon nanotubes (MWCNTs) included in biodiesel-blended diesel fuel using response surface method (RSM). The influence of input parameters —engine load and MWCNTs concentration — on the response parameters (i.e., BSFC, BTE, CO, NOX, and UHC) were investigated and predicted. MWCNTs were added into B20 fuel (20% biodisesel+80% diesel) in various concentrations (25, 50, 75, and 100 ppm). The tests performed under varying engine load conditions (5, 10, 15, and 20 Nm) at a constant engine speed of 1800 rpm. Multi-regression models for BTE, BSFC, and CO, UHC, and NOX emissions were derived using RSM and were found to be statistically significant. Exhaust UHC and CO concentrations for the studied fuel blend decreases with the addition of MWCNTs into B20 fuel, while NOx emissions drastically increased. The optimal engine working conditions were found to be an engine load of 10 Nm and MWCNTs concentration of 98 ppm. Based on the optimized values, the most optimal results for BTE and BSFC along with CO, UHC, and NOX emissions were found to be 28.57 (%), 269.84 (g/kWh), 0.03 (%Vol.), 44.16 (ppm), and 458.81 (ppm).