Performance and emission characteristics of a CI engine using nano particles additives in biodiesel-diesel blends and modeling with GP approach

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@Article{Ghanbari:2017:Fuel,
  author =       "M. Ghanbari and G. Najafi and B. Ghobadian and 
                 T. Yusaf and A. P. Carlucci and M. Kiani Deh Kiani",
  title =        "Performance and emission characteristics of a {CI}
                 engine using nano particles additives in
                 biodiesel-diesel blends and modeling with {GP}
                 approach",
  journal =      "Fuel",
  year =         "2017",
  ISSN =         "0016-2361",
  DOI =          "doi:10.1016/j.fuel.2017.04.117",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0016236117305380",
  abstract =     "The performance and the exhaust emissions of a diesel
                 engine operating on nano-diesel-biodiesel blended fuels
                 has been investigated. Multi wall carbon nano tubes
                 (CNT) (40, 80 and 120 ppm) and nano silver particles
                 (40, 80 and 120 ppm) were produced and added as
                 additive to the biodiesel-diesel blended fuel. Six
                 cylinders, four-stroke diesel engine was fuelled with
                 these new blended fuels and operated at different
                 engine speeds. Experimental test results indicated the
                 fact that adding nano particles to diesel and biodiesel
                 fuels, increased diesel engine performance variables
                 including engine power and torque output up to 2percent
                 and brake specific fuel consumption (bsfc) was
                 decreased 7.08percent compared to the net diesel fuel.
                 CO2 emission increased maximum 17.03percent and CO
                 emission in a biodiesel-diesel fuel with nano-particles
                 was lower significantly (25.17percent) compared to pure
                 diesel fuel. UHC emission with silver
                 nano-diesel-biodiesel blended fuel decreased
                 (28.56percent) while with fuels that contains CNT nano
                 particles increased maximum 14.21percent. With adding
                 nano particles to the blended fuels, NOx increased
                 25.32percent compared to the net diesel fuel. This
                 study also presents genetic programming (GP) based
                 model to predict the performance and emission
                 parameters of a CI engine in terms of nano-fuels and
                 engine speed. Experimental studies were completed to
                 obtain training and testing data. The optimum models
                 were selected according to statistical criteria of root
                 mean square error (RMSE) and coefficient of
                 determination (R2). It was observed that the GP model
                 can predict engine performance and emission parameters
                 with correlation coefficient (R2) in the range of
                 0.93-1 and RMSE was found to be near zero. The
                 simulation results demonstrated that GP model is a good
                 tool to predict the CI engine performance and emission
                 parameters.",
  keywords =     "genetic algorithms, genetic programming, Nano
                 additives, Diesel-biodiesel blends, Ultrasonic",
}

Genetic Programming entries for M Ghanbari GholamHasan Najafi Barat Ghobadian Talal Yusaf Antonio Paolo Carlucci Mostafa Kiani Deh Kiani

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