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Rovira-Esteva M.,ETSEIB | Rovira-Esteva M.,Polytechnic University of Catalonia | Pardo L.C.,ETSEIB | Pardo L.C.,Polytechnic University of Catalonia | And 2 more authors.
NATO Science for Peace and Security Series A: Chemistry and Biology | Year: 2010

The temperature dependence of structural parameters of orientational glasses of the halogenomethane family, Freon 112 (FCl 2C)-(CCl 2F)) and Freon 112a (F 2ClC)-(CCl 3)) are studied at short- (molecular) intermediate- (orientational correlations) and long-range (lattice parameters) scales by means of neutron diffraction. The two materials which are chemical isomers display strikingly different properties in their ordering patterns resulting from a shift in balance between electrostatic and excluded-volume interaction. The relevance of these findings to our understanding of glassy phenomena is discussed.


Jaboulay J.-C.,CEA Saclay Nuclear Research Center | Li Puma A.,CEA Saclay Nuclear Research Center | Martinez Arroyo J.,ETSEIB
Fusion Engineering and Design | Year: 2013

SYCOMORE, a fusion reactor system code based on a modular approach, is under development at CEA. In this framework, this paper describes a methodology developed to build the neutronic module of SYCOMORE. This neutronic module aims to evaluate main neutronic parameters characterising a fusion reactor (tokamak): tritium breeding ratio, multiplication factor, nuclear heating as a function of the reactor main geometrical parameters (major radius, elongation, etc.), of the radial build, Li enrichment, blanket and shield thickness, etc. It is based on calculations carried out with APOLLO2 and TRIPOLI-4 CEA transport code on simplified 1D and 2D neutronic models. These models are validated versus a more detailed 3D Monte-Carlo model (using TRIPOLI-4). To ease the integration of this neutronic module in SYCOMORE and provide results instantly, a surrogate model that replicates the 1D and 2D neutronic model results was used. Among the different surrogate models types (polynomial interpolation, responses functions, interpolating by Kriging, artificial neural network, etc.) the neural networks were selected for their efficiency and flexibility. The methodology described in this paper to build SYCOMORE neutronic module is devoted to HCLL blanket, but it could be applied to any breeder blanket concept provided that appropriate validation could be carried out. © 2013 Elsevier B.V.

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