A Statistical Analysis of the Scaling Laws for the Confinement Time Distinguishing between Core and Edge
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- @Article{Peluso:2015:PP,
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author = "E. Peluso and M. Gelfusa and A. Murari and
I. Lupelli and P. Gaudio",
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title = "A Statistical Analysis of the Scaling Laws for the
Confinement Time Distinguishing between Core and Edge",
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journal = "Physics Procedia",
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volume = "62",
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pages = "113--117",
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year = "2015",
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note = "3rd International Conference Frontiers in Diagnostic
Technologies, ICFDT3 2013, 25-27 November 2013,
Laboratori Nazionali di Frascati, Italy",
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ISSN = "1875-3892",
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DOI = "doi:10.1016/j.phpro.2015.02.020",
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URL = "http://www.sciencedirect.com/science/article/pii/S1875389215000516",
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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.",
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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