Bremen 2017 – wissenschaftliches Programm

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P: Fachverband Plasmaphysik

P 15: Helmholtz Graduate School II

P 15.14: Poster

Dienstag, 14. März 2017, 16:30–18:30, HS Foyer

THEODOR in a Bayesian Framework: a probabilistic evaluation of heat flux density profiles — •Dirk Nille, Udo v. Toussaint, and Bernhard Sieglin — Max-Planck-Institute for Plasma Physics, Boltzmannstr. 2, D-85748 Garching, Germany

The ill-posed problem of estimating parameters from quantities which are subject to diffusion is of central importance for various transport models in physics. In fusion research a precise determination of the heat flux density onto the surface of a solid material is crucial, as plasma power exhaust is a major challenge in the development of a future fusion power plant.

This is done by solving the heat diffusion equation in the target material with the surface temperature as boundary condition, given by measurements. Infrared thermography provides spatially and temporally resolved data for this purpose. Solving the heat diffusion equation is tackled for decades by deterministic codes like THEODOR. Developed for the fast evaluation of data no statistical analysis was performed. Error bars are obtained from the standard deviation during quasi-static conditions.

Using adaptive kernel to model the heat flux density distribution onto the surface and taking into account the known distribution of the measured photon flux yields reconstructions of better quality and known uncertainty. Therefore the numerical method of THEODOR is used in a forward model.