New correlations for predicting pure and impure natural gas viscosity

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@Article{Izadmehr:2016:JNGSE,
  author =       "Mojtaba Izadmehr and Reza Shams and 
                 Mohammad Hossein Ghazanfari",
  title =        "New correlations for predicting pure and impure
                 natural gas viscosity",
  journal =      "Journal of Natural Gas Science and Engineering",
  volume =       "30",
  pages =        "364--378",
  year =         "2016",
  ISSN =         "1875-5100",
  DOI =          "doi:10.1016/j.jngse.2016.02.026",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1875510016300713",
  abstract =     "Accurate determination of natural gas viscosity is
                 important for successful design of production,
                 transportation, and gas storage systems. However, most
                 of available models/correlations suffer from
                 complexity, robustness, and inadequate accuracy
                 especially when wide range of pressure and temperature
                 is applied. Present study illustrates development of
                 two novel models for predicting natural gas viscosity
                 for pure natural gas (CH4) as well as natural gas
                 containing impurities. For this purpose, 6484 data
                 points have been gathered and analysed from the open
                 literature covering wide range of pressure,
                 temperature, and specific gravity levels, temperature
                 ranges from -262.39 to 620.33 degree F (109.6 to 600
                 K), pressure ranges from 1.4508 to 29,000 psi
                 (0.0100-199.94801 MPa), and gas specific gravity ranges
                 from 0.553 to 1.5741. Sensitivity analysis on the
                 collected data points through design of experiments
                 algorithm showed that pseudo reduced pressure and
                 pseudo reduced temperature are the most effective
                 parameters as the inputs of the models. The Leverage
                 Value Statistics is applied and doubtful data points
                 are determined. The average absolute relative error and
                 the coefficient of determination of the proposed models
                 for predicting pure/impure natural gas viscosity on a
                 wide range of conditions are 5.67percent and
                 1.87percent, 0.9826 and 0.9953, respectively. Reliable
                 accuracy of proposed models in comparison to eight
                 commonly used correlations makes them attractive for
                 possible implementing in natural gas
                 simulation/modelling applications.",
  keywords =     "genetic algorithms, genetic programming, Pure/impure
                 natural gas viscosity, New correlations, Empirical
                 models, Design of experiments, Leverage value
                 statistics",
}

Genetic Programming entries for Mojtaba Izadmehr Reza Shams Mohammad Hossein Ghazanfari

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