A Statistical Analysis of the Scaling Laws for the Confinement Time Distinguishing between Core and Edge

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@Article{Peluso:2015:PP,
  author =       "E. Peluso and M. Gelfusa and A. Murari and 
                 I. Lupelli and P. Gaudio",
  title =        "A Statistical Analysis of the Scaling Laws for the
                 Confinement Time Distinguishing between Core and Edge",
  journal =      "Physics Procedia",
  volume =       "62",
  pages =        "113--117",
  year =         "2015",
  note =         "3rd International Conference Frontiers in Diagnostic
                 Technologies, ICFDT3 2013, 25-27 November 2013,
                 Laboratori Nazionali di Frascati, Italy",
  ISSN =         "1875-3892",
  DOI =          "doi:10.1016/j.phpro.2015.02.020",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1875389215000516",
  abstract =     "The H mode of confinement in Tokamaks is characterized
                 by a thin region of high gradients, located at the edge
                 of the plasma and called the Edge Transport Barrier.
                 Even if various theoretical models have been proposed
                 for the interpretation of the edge physics, the main
                 empirical scaling laws of the plasma confinement time
                 are expressed in terms of global plasma parameters and
                 they do not discriminate between the edge and core
                 regions. Moreover all the scaling laws are assumed to
                 be power law monomials. In the present paper, a new
                 methodology is proposed to investigate the validity of
                 both assumptions. The approach is based on Symbolic
                 Regression via Genetic Programming and allows first the
                 extraction of the most statistically reliable models
                 from the available experimental data in the ITPA
                 database. Non linear fitting is then applied to the
                 mathematical expressions found by Symbolic regression.
                 The obtained scaling laws are compared with the
                 traditional scalings in power law form.",
  keywords =     "genetic algorithms, genetic programming, H mode
                 scaling, symbolic regression, edge and core
                 confinement",
}

Genetic Programming entries for Emmanuele Peluso M Gelfusa A Murari I Lupelli P Gaudio

Citations