• Title of article

    Plasma diagnostics at Aditya Tokamak by two views visible light tomography

  • Author/Authors

    Goswami، نويسنده , , Mayank and Munshi، نويسنده , , Prabhat and Saxena، نويسنده , , Anupam and Kumar، نويسنده , , Manoj and Kumar، نويسنده , , Ajai، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    7
  • From page
    2659
  • To page
    2665
  • Abstract
    This visible light computerized tomography exercise is a part of a project to establish an auxiliary imaging method to assist other imaging facilities at the Institute of Plasma Research (IPR), India. Space constraints around Aditya Tokamak allow only two orthogonal ports. Each port has one detector array (64 sensors) sensitive to the visual spectrum emitted by Hα emission. The objective here is to report the developments on limited view tomography for hot plasma imaging. Spatially filtered entropy maximization algorithm with non-uniform discretization grids is employed. Estimation of unique kernel smoothening parameters (mask size and exponent factor) depends on entropy function and projection data. It removes requirement of any arbitrary/user-based decision for choosing a regularization factor thus minimizes the chance for biasedness or errors. Synthetic projection data is used to analyse the performance of this modification. The error band in the process of recovery remains under acceptable level (less than 15%) irrespective of the origin of the emissions from the core. Reconstructed hot plasma images/profiles from Aditya Tokamak are shown. These profiles may improve the current understanding about (a) plasma–wall interaction or edge plasma turbulence, (b) control and generation of plasma and (c) correlations between theoretical and engineering advancements in Tokamak reactors.
  • Keywords
    Visible light tomography , adaptive algorithm , Plasma Diagnostics
  • Journal title
    Fusion Engineering and Design
  • Serial Year
    2014
  • Journal title
    Fusion Engineering and Design
  • Record number

    2370862