Optimizing a Thomson scattering diagnostic for fast dynamics and high background
Rev. Sci. Instrum. 79, 10E735 (2008); doi:10.1063/1.2957844
Published 31 October 2008
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The Madison Symmetric Torus (MST) presents challenging conditions for Thomson scattering (TS) measurements. The MST plasmas are reversed-field pinches (RFPs) with electron density ne<3×1013 cm−3, typically 1×1013 cm−3. The TS system was designed to measure from 10 eV to 2 keV; however, six polychromators were upgraded from four to eight spectral channels to resolve to 10 keV. There is no diverter or vertical field, so wall interaction results in high background light both from ion and neutral bremsstrahlungs and from line radiation. Also during standard plasmas, the RFP exhibits regular reconnection sawteeth events during which the plasma current, density, and temperature profiles are flattened. These events are of interest both due to the reconnection physics and to their contribution to the MST equilibrium and confinement. These events occur over 100 µS and exhibit large changes in background light and fast changes in temperature. During improved confinement plasmas, there are no sawteeth; the background is low but the temperature can be over an order of magnitude higher. Data analysis of the system has been developed to accommodate both the large dynamic range of the temperature, the fast dynamics, and the fast changing, high amplitude background. Special attention has been paid to the sources of error, in particular, the contribution of the background. A response-function method reduces the measured uncertainty by a factor of 2. Numerical techniques have been developed which are extremely robust. Two methods are used, a conventional
2 minimization using a Levenberg–Marquardt algorithm coupled with Monte Carlo modeling for the error bar and a Bayesian statistics method. The Bayesian method computes the probability distribution for the measured photons and electron temperature and this information can be used to ensemble data and will allow future integrated data analysis efforts.
©2008 American Institute of Physics
2 minimization using a Levenberg–Marquardt algorithm coupled with Monte Carlo modeling for the error bar and a Bayesian statistics method. The Bayesian method computes the probability distribution for the measured photons and electron temperature and this information can be used to ensemble data and will allow future integrated data analysis efforts.
©2008 American Institute of Physics
| History: | Presented 13 May 2008; received 12 May 2008; accepted 9 June 2008; published 31 October 2008 |
| Permalink: |
http://link.aip.org/link/?RSINAK/79/10E735/1 |
KEYWORDS and PACS
PUBLICATION DATA
0034-6748 (print)
1089-7623 (online)
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