Development of empirical models with high accuracy for estimation of drag coefficient of flow around a smooth sphere: An evolutionary approach

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@Article{Barati:2014:PT,
  author =       "Reza Barati and 
                 Seyed Ali Akbar {Salehi Neyshabouri} and Goodarz Ahmadi",
  title =        "Development of empirical models with high accuracy for
                 estimation of drag coefficient of flow around a smooth
                 sphere: An evolutionary approach",
  journal =      "Powder Technology",
  volume =       "257",
  pages =        "11--19",
  year =         "2014",
  ISSN =         "0032-5910",
  DOI =          "doi:10.1016/j.powtec.2014.02.045",
  URL =          "http://www.sciencedirect.com/science/article/pii/S003259101400182X",
  keywords =     "genetic algorithms, genetic programming, Particle
                 motion, Sphere drag, Reynolds number",
  abstract =     "An accurate correlation for the smooth sphere drag
                 coefficient with wide range of applicability is a
                 useful tool in the field of particle technology. The
                 present study focuses on the development of high
                 accurate drag coefficient correlations from low to very
                 high Reynolds numbers (up to 1000000) using a
                 multi-gene Genetic Programming (GP) procedure. A clear
                 superiority of GP over other methods is that GP is able
                 to determine the structure and parameters of the model,
                 simultaneously, while the structure of the model is
                 imposed by the user in traditional regression analysis,
                 and only the parameters of the model are assigned. In
                 other words, in addition to the parameters of the
                 model, the structure of it can be optimised using GP
                 approach. Among two new and high accurate models of the
                 present study, one of them is acceptable for the region
                 before drag dip, and the other is applicable for the
                 whole range of Reynolds numbers up to 1 million
                 including the transient region from laminar to
                 turbulent. The performances of the developed models are
                 examined and compared with other reported models. The
                 results indicate that these models respectively give
                 16.2percent and 69.4percent better results than the
                 best existing correlations in terms of the sum of
                 squared of logarithmic deviations (SSLD). On the other
                 hand, the proposed models are validated with
                 experimental data. The validation results show that all
                 of the estimated drag coefficients are within the
                 bounds of 7percent of experimental values.",
}

Genetic Programming entries for Reza Barati Seyed Ali Akbar Salehi Neyshabouri Goodarz Ahmadi

Citations