Multichannel fluctuation data analysis by the singular value decomposition method. Application to MHD modes in JET

Abstract

Abstracl-The spatial stru~turr and temporal ewlulion ofcohcrent M H D modes in ruusion plasma dcvicrs havc been so far infcrrcd from the experimental signals hy using spectral techniques. Considering the data as B collcctioii o f n-dimensional discrcte limc scrics n,(r) permits one IO introduce in this C O ~~C X I B sign;d processing method based on the Singular Vnlup Decomposirivrr (SVD) o f a rectangulnr matrix.This paper shows that, whereas the SVD is equivalcnt lo the discrete Fourier transform in the case of travelling sinusoidal W B V C S . in mort realistic CBSCS il i s a clear improvement on the spcctral methods, since i t disentangles thc poloidal structure wilhoul n priori knowledgc. Various applications of SVD, first on artificial signels and then on magnetic and SXR signals dctccted in the JET Tokamak in scveiai olasma regimes, arc shown with lhe purposc of illUStrdling the powcr and limits of Ihe method.

The effect of limiter biasing on the plasma edge rotation and MHD activities

“…2 only one coil from a poloidal array of 12 MHD coils is shown. Singular Value Decomposition (SVD) [16][17] and the Fourier coefficient decomposition (FCD) 18 have been used for extracting spatial and temporal mode structures m=1-4. In this shot, the MHD activity is week without bias and it is excited with bias.…”

Reduction of magnetic confinement fusion data for data mining applications

“…Here a two step process is suggested which extends the one step svd approach describe by Nardone [8]. In the first step a svd is used to extract the main spatial components or modes of short size, strong power time segments.…”

“…The svd also recovers travelling waves with real valued amplitudes as a sum of two standing waves that are phase shifted by π/2. The application of the svd approach was investigated for plasma experiments at jet [8] and has since been successfully applied to other Tokamak devices [3]. The svd is widely used in many areas of data analysis and is very popular due to availability of robust and efficient numerical algorithms.…”

Analysis of disruptive discharges during density limit experiments on the HT-7 Tokamak

“…The spatial structure and temporal evolution of coherent MHD modes observed in the HT-7 superconducting tokamak have been inferred from the experimental signals by using spectral techniques. Using multichannel fluctuation data analysis by the singular value decomposition method (SVD) [15][16], the poloidal number m is obtained. Fig.…”