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 Michela Gelfusa Andrea Murari I Lupelli P Gaudio

Citations