IFA - CEA Project

Project code: III.1

Project acronym: TomoModelSupra

Field: Fundamental research on Energy

Topic: Nuclear fusion and fission

 

Project title

Characterisation and modelisation of superconductor cables:
accurate 3D examination of Superconductor Cables by X-ray microtomography and mutliphysic models upgrade
(electromagnetic, thermo-hydraulic and mechanic)

Partners

 

RO team

CEA team

Project leader Name

Ion TISEANU

Louis ZANI

Laboratory

Institution

Address

Tel :
Fax :
E-mail:

Head of laboratory

Plasma Physics and Nuclear Fusion

National Institute for Lasers, Plasma and Radiation Physics (INFLPR)
Atomistilor Str. 409, P.O. Box. MG-36 
077125, Bucharest-Magurele, ROMANIA
+4021-4574051
+4021-4574243
tiseanu@infim.ro

Dr. Ion TISEANU

Institut de Recherche sur la Fusion par confinement Magnétique (IRFM)
Commissariat à l’Energie Atomique et aux Energies Alternatives (CEA)
Centre de Cadarache
13108 St Paul Lez Durance FRANCE
+33442254967
+33442252661
louis.zani@cea.fr

Dr. Alain Becoulet

Project Objectives

Abstract

Operation and data acquisition of an X-ray micro-tomograph developed at INFLPR are optimized to produce stacks of 2-D high-resolution tomographic sections of Cable in Conduit Conductor (CICC) type superconductors demanded in major fusion projects. High-resolution images for CCIC samples (486 NbTi&Cu strands of 0.81 mm diameter, jacketed in rectangular stainless steel pipes of 22x26 mm^2) are obtained by a combination of high energy/ high intensity and small focus spot X-ray source and high resolution /efficiency detector array. The stack of reconstructed slices is the input data for quantitative analysis consisting of accurate strands positioning, determination of the local and global void fraction and 3D strand trajectory assignment for relevant fragments of cable (~300 mm). Strand positioning algorithm is based on the application of Gabor Annular filtering followed by local maxima detection. The local void fraction is extensively mapped by employing local segmentation methods at a space resolution of about 50 sub-cells sized to be relevant to triplet of triplet twisting pattern.
For the strand trajectory assignment we implemented two types of algorithms: i) a simple local algorithm trying to match the strands in adjacent slices. Even with a strand positioning efficiency over 95% such a simple algorithm cannot assign more than 50% of strands trajectories; ii) a global algorithm of the linear programming type which provides dramatically improved number of strand trajectories. For the benchmark CCIC samples 99% of the trajectories are correctly assigned. For production samples the efficiency of the algorithm is around 90%. Trajectory assignment of a high proportion of the strands is a crucial result for the derivation of statistical properties of the cable such as twisting pattern, cos(theta) or void fraction.

 

Top

Back to tomography.inflpr.ro


Site designed and maintained by Cosmin Dobrea